Data Analytics training in Hyderabad, Ameerpet
Comprehensive
Curriculum
- Learn Data Analytics, Data Visualisation, SQL, Statistics, CCE, IIT etc. Data, and more
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SQL , Data Wrangling ,Data Analysis,Prediction algorithms ,Data visualization ,Time Series ,Machine Learning ,PowerBI ,Advanced Statistics ,Data Mining ,R Programming
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Data Analytics training in Hyderabad ,Ameerpet
Personalised
Mentorship
- Hands-on projects under the guidance of industry experts
- Deepen your expertise by working on online data Analytics lab sessions
- 1:1 personalized mentorship
Data Analytics training in Hyderabad
Dedicated Career
Assistance
- Exclusive campus hiring drives with leading analytics companies
- Job opportunities shared by 350+ companies
- 1:1 Career mentorship, access to job boards and more
Data Analytics Course Training
Live Online Classes | 3 Months
Upcoming Batch Schedule for Data Analytics Course.
Sri VidyaTechnologies provides flexible timings to all our students. Here is the Data Analytics Course Training Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.
 06-03-2022 | Monday (Monday - Friday) Weekdays Regular | 08:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session | Course Fees |
| 13-03-2022 | Monday (Monday - Friday) Weekdays Regular | 11:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session | Course Fees |
| 20-03-2022 | Monday (Monday - Friday) Weekdays Regular | 10:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session | Course Fees |
| 27-03-2022 | Monday (Monday - Friday) Weekdays Regular | 10:00 AM (IST) (Class 1Hr - 1:30Hrs) / Per Session | Course Fees |
Sri Vidya Technologies Certificate
Curriculum
The curriculum has been designed by faculty at Sri Vidya Tech Data Analytics training in Hyderabad and leading industry leaders. The teaching, content and projects in the course are by world-renowned faculty and other practicing management professionals from leading companies.
Module 1 – Preparatory Sessions – Data Transformation using Ms. Excel & Python
Learn how to do data analysis, data transformation and other important data analysis functions. Basic fundamental of Python and learn how to do data analytics using the same.
Module 2 – Data wrangling with SQL
Introduction to SQL
2.2 Database normalization
2.3 Entity-relationship model
2.4 SQL operators
2.5 Join, tables, and variables
2.6 SQL functions
2.7 Subqueries
2.8 SQL functions, views, and stored procedures
2.9 User-defined functions
2.10 SQL performance and optimization
2.11 Advanced concepts
- Correlated sub query
- Grouping sets
Module 3 – Presto
3.1 Introduction to Presto
3.2 Writing Queries in Presto on large data sets.
3.3 Data Transformation using Presto
Module 4 – Introduction to Data Science & Statistics
4.1 Descriptive Statistics
- Mean
- Median
- Mode
- Tables
- Charts
4.2 Introduction to Probability
- Probability in Business Analytics
4.3 Probability Distributions
- Binomial distribution
- Poisson distribution
- Normal distribution
4.4 Hypothesis Testing and Estimation
- Hypothesis testing
- Estimation
4.5 Goodness of Fit
- How the sample adequately fits a distribution from an observational set
Module 5 – Business Problem Solving, Insights and Storytelling
5.1 Business domains
- Finance
- Marketing
- Retail
- Supply Chain
5.2 Understanding the business problem and formulating hypotheses
5.3 Exploratory data analysis
5.4 Data storytelling: Narrate stories in a memorable way
5.5 Project on deriving business insights and storytelling
Module 6 – Optimization Techniques
6.1 Linear programming
6.2 Goal programming
6.3 Integer programming
6.4 Mixed integer programming
6.5 Distribution and network models
Module 7 - KNIME
7.1 Introduction to KNIME
7.2 Working with data in KNIME
7.3 Loops in KNiME
7.4 Webscraping in KNIME
7.5 Hyperparameter optimization in KNIME
7.6 Hyperparameter optimization for Machine Learning Models using loops in KNIME
7.7 Feature Selection in KNIME
Module 8 – Statistics & Machine Learning using R Programming
8.1 Programming with R
8.2 Advance Statistics
- ANOVA
- Regression analysis
- Dimension reduction techniques
8.3 Data Mining
- Supervised and unsupervised learning
- Clustering
- Market Basket Analysis
- Decision trees
- Random forest
- Neural networks
Data Analytics with SAS Training Syllabus
Module 1: Overview of SAS
- Introduction and History of SAS
- Significance of SAS software solutions in various industries
- Demonstrate SAS Capabilities
- Job Profile / career opportunities with SAS worldwide?
Module 2: Base SAS Fundamentals
- Explore SAS Windowing Environment
- SAS Tasks
- Working with SAS Syntax
- Create and submit a SAS sample program
Module 3: Data Access & Data Transformation
- Accessing SAS Data libraries
- Getting familiar with SAS Data set
Module 4: Reading SAS data set
- Introduction to reading data
- Examine structure of SAS data set
- Understanding of SAS works
Module 5: Reading Excel worksheets
- Using Excel data as input
- Create as sample program to import and export excel sheets
Module 6: Reading Raw data from External File
- Introduction to raw data
- Reading delimited raw data file (List Input)
- Using standard delimited data as input
- Using nonstandard delimited data as input
- Reading raw data aligned to columns (Fixed or column input)
- Reading raw data with special instructions (Formatted input)
Module 7: Writing to an External file
- Write data values from SAS data set to an external file
Module 8: Data transformations (Data step processing)
- Create multiple output datasets from single SAS dataset
- Writing observations to one or more SAS datasets
- Controlling which observations and variables to be written to output data
Module 9: Creating subset of observations using
- Where condition
- Conditional processing using: IF statements
Module 10: Processing Data Iteratively
- Iterative DO loop processing with END statement
- DO WHILE & DO UNTIL Statement
- SAS Array statement
Module 11: Summarizing data
- Creating and Accumulating total variable (Retain)
- Using Assignment statement
- Accumulating totals for a group of data (BY group)
Module 12: Manipulating Data
- Sorting SAS data sets
- Manipulating SAS data values
- Presentation of user defined values /data/currency values using FORMAT procedure
- SAS functions to manipulate char and num data
- Convert data type form char-to num and num-to-char
- SAS variables lists/ SAS variables lists range
- Debugging SAS program
- Accessing observations by creating index
Module 13: Restructuring a SAS data set
- Rotating with the data step
- Using the transpose procedure
Module 14: Combining SAS data sets
- Concatenation
- Interleaving
- One to one reading
- One to one merging (with non-matching)
- Match merging (Merging types with IN=option)
Module 15: SAS Access & SAS Connect
- Validating and cleaning data
- Detect and correct syntax errors
- Examining data errors
Module 16: Analysis & Presentation
- SAS/REPORTS SAS/GRAPH
- SAS/STATS SAS/ODS
Module 17: Producing detailed /Summary Reports
- Freq Report
- Means Report
- Tabulate Report
- Proc report
- Summary report
- Univariate report
- Contents report
- Print report
- Compare proc
- Copy proc
- Datasets proc
- Proc append
- Proc delete
Module 18: Generating Statistical Reports using
- Regression proc
- Uni/Multivariate proc
- Anova proc
Module 19: Generating Graphical reports using
- Producing Bar and Pie charts (GCHART Proc)
- Producing plots (GPLOT Proc)
- Presenting Output Report result in:
- Text files
- Excel
- HTML Files
Module 20: SAS/SQL Programming
- Introduction and overview to SQL procedure
- Proc SQL and Data step comparisons
Module 21: Basics Queries
- Proc SQL syntax overview
- Specifying columns/creating new columns
- Specifying rows/subsetting on rows
- Ordering or sorting data
- Formatting output results
- Presenting detailed data
- Presenting summarized data
Module 22: Sub Queries
- Non correlated sub queries
- Correlated sub queries
Module 23: SQL Joins (Combining SAS data sets using SQL Joins)
- Introduction to SQL joins
- Types of joins with examples
- Simple to complex joins
- Choosing between data step merges and SQL joins
Module 24: SET Operators
- Introduction to set operations
- Except/Intersect/Union/Outer union operator
Module 25: Additional SQL Procedures features
- Creating views with SQL procedure
- Dictionary tables and views
- Interfacing Proc SQL with the macro programming language
- Creating and maintaining indexes
- SQL Pass-Through facility
Module 26: SAS Macro Language
- Introduction to macro facility
- Generate SAS code using macros
- Macro compilation
- Creating macro variables
- Scope or macro variables
- Global/Local Macro variables
- User defined /Automatic Macro variables
- Macro variables references
- Combing macro variables references with text
- Macro functions
- Quoting (Masking)
- Creating macro variables in Data step (Call SYMPUT Routine)
- Obtaining variable value during macro execution (SYMGET function)
- Creating macro variables during PROC SQL execution (INTO Clause)
- Creating a delimited list of values
- Macro parameters
- Strong Macro using Autocall Features
- Permanently storing and using stored compiled macro program
- SAS Macro debugging options to track problems
Module 27: Basics Statistics
- Standard deviation
- Correlation Coefficients
- Outliers
- Linear regressions
- Clustering
- Chi Square
Data Analytics with SQL Training Syllabus
Module 1: Predictive Modeling
. Multiple linear regression
. Logistic regression
. Linear discriminant analysis
Module 2: Time-Series Forecasting
. Introduction to time-series
. Correlation
. Forecasting
. Auto regressive models
Module 3: Feature Engineering
. Handling unstructured data
. Machine Learning algorithms
. Bias variance trade-off
. Handling unbalanced data
. Boosting
. Model validation
Module 4: Advance Machine Learning Techniques
. Hyper parameter optimization
. Advance Machine Learning Libraries – XGBoost
. Solving Problems on Gaggle
Module 5: Data Science Execution Strategy
. Framework to Data Science strategy
. Mapping Data Science with data architecture strategy
. Executing Data Science strategy
Module 6: Business Case Studies
. Marketing & retail analytics
. Social analytics
. Logistics & supply chain
. Financial analytics
Module 7: Statistics Basics
- Central Tendency
- Mean
- Median
- Mode
- Skewness
- Normal Distribution
- Probability Basics
- What does mean by probability?
- Types of Probability
- ODDS Ratio?
- Standard Deviation
- Data deviation & distribution
- Variance
- Bias variance Trade off
- Underfitting
- Overfitting
- Distance metrics
- Euclidean Distance
- Manhattan Distance
- Outlier analysis
- What is an Outlier?
- Inter Quartile Range
- Box & whisker plot
- Upper Whisker
- Lower Whisker
- Scatter plot
- Cook’s Distance
- Missing Value treatments
- What is a NA?
- Central Imputation
- KNN imputation
- Dummification
- Correlation
- Pearson correlation
- Positive & Negative correlation
Module 8: Error Metrics
- Classification
- Confusion Matrix
- Precision
- Recall
- Specificity
- F1 Score
- Regression
- MSE
- RMSE
- MAPE
Module 9:Visualization using Power BI
. Introduction to Power BI
. Data Extraction
. Data Transformation – Shaping & Combining Data
. Data Modelling & DAX
. Data Visualization with analytics
. Power BI Service (Cloud), Q&A, and Data Insights
. Power BI Settings, Administration & Direct Connectivity
. Embedded Power BI with API & Power BI
. Power BI Advance & Power BI Premium
Module 10: Data Science Capstone Project
In the Data Science & Business Analytics Capstone project, you will use all the knowledge and skills you have acquired throughout this advanced certification program and get real world Industry project exposure.
Data Analytics : About Trainer
Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.
- More than 7+ Years of Experience.
- Trained more than 2000+ students in a year.
- Strong Theoretical & Practical Knowledge.
- Certified Professionals with High Grade.
- Well connected with Hiring HRs in multinational companies.
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
- Trainers have Experienced on multiple real-time projects in their Industries.
- Our Trainers are working in multinational companies such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc
Trainer Profile of Data Analytics Course
We choose the best trainers for you. The best thing about taking Data Analytics Training at Sri Vidya Technologies is certainly the trainers here. They are the best you can avail of and will take care of all your academic needs. The best thing about the approach with which they impart training to the candidates is that its student-centric. That means the training imparted to you is based on your needs, demands and comfort level. The teachers do their best to make sure their knowledge and wisdom in the field of data science get effortlessly passed on to you. They don’t just have immense theoretical knowledge but also a lot of practical experience to enrich you with.
- Our trainers are industry data experts who work in Data Analytics.
- Most of our trainers work in companies and have considerable work experience in Data Analytics field.
- Our trainers are flexible and are available based on your timings
- Our trainers have good experience in training and are good at demonstrating the solution for real-world data Analytics problems.
Data Analytics : About Trainer
Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.
- More than 7+ Years of Experience.
- Trained more than 2000+ students in a year.
- Strong Theoretical & Practical Knowledge.
- Certified Professionals with High Grade.
- Well connected with Hiring HRs in multinational companies.
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
- Trainers have Experienced on multiple real-time projects in their Industries.
- Our Trainers are working in multinational companies such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc
Trainer Profile of Data Analytics Course
We choose the best trainers for you. The best thing about taking Data Analytics Training at Sri Vidya Technologies is certainly the trainers here. They are the best you can avail of and will take care of all your academic needs. The best thing about the approach with which they impart training to the candidates is that its student-centric. That means the training imparted to you is based on your needs, demands and comfort level. The teachers do their best to make sure their knowledge and wisdom in the field of data science get effortlessly passed on to you. They don’t just have immense theoretical knowledge but also a lot of practical experience to enrich you with.
- Our trainers are industry data experts who work in Data Analytics.
- Most of our trainers work in companies and have considerable work experience in Data Analytics field.
- Our trainers are flexible and are available based on your timings
- Our trainers have good experience in training and are good at demonstrating the solution for real-world data Analytics problems.
Key Features of Data Analytics Training
Introduction to Data Analytics
This course presents a gentle introduction into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining. You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.
This course will help you to differentiate between the roles of a Data Analyst, Data Scientist, and Data Engineer. You will learn the responsibilities of a Data Analyst and exactly what data analysis entails. You will be able to summarize the data ecosystem, such as databases and data warehouses. You will then uncover the major vendors within the data ecosystem and explore the various tools on-premise and in the cloud. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you will be able to visualize the daily life of a Data Analyst, understand the different career paths that are available for data analytics, and identify the many resources available for mastering this profession.
This course is part of multiple programs
- IBM Data Analytics with Excel and R Professional Certificate
- IBM & Darden Digital Strategy Specialization
- Data Analysis and Visualization Foundations Specialization
- IBM Data Analyst Professional Certificate
What is Data Analytics?
The field of data science is interdisciplinary, which encompasses a lot of areas including scientific methods, processes, systems, and algorithms. This field is deeply connected with big data and analytics. With proper training in data science, you make yourself eligible for recruitment in a lot of companies that have data handling jobs available with them. The world has been taken over by big data. And with the foothold of big data growth in the world, the need for its storage began to grow. Enterprise industries saw it as a challenge till somewhere around 2010. At that time, more emphasis was being laid on building solutions and frameworks for the storage of data. Then came frameworks like Hadoop that indeed solved the problem of data storage.
But then a new problem arose- processing of this stored data. Here comes the role of data science. In Hollywood sci-fi movies, you see a lot of seemingly unrealistic ideas. Believe it or not, all such ideas can be turned into reality with the help of data science. In another way, you can say that the future of artificial intelligence lies in data science. And that is probably the reason why data science and its courses are so much in demand. People want to learn it for lucrative IT career options. So, data science, which is a concoction of machine learning principles, algorithms, and various tools, is used to figure out concealed patterns in raw data. It is because of data science that data can be used to add value to any business. Predictive causal analytics, prescriptive analytics, and machine learning are the elements that together render data science helpful in making decisions and predictions. Here, it would be valuable to add that the future lies in the hands of data scientists. The need for data scientists that have expertise over the subject is growing with each passing day. What more? Well, data science is changing the way people look at the world flooded with data.
What skills are needed to be a Data Analytics?
- A data scientist Analytics should be an expert in multiple skills such as Mathematics, statistics, Big Data.
- Data Analysis should have a deeper understanding of Mathematics, Statistics and should have good analytical skills to understand patterns in these data.
- We should be able to develop machine learning algorithms that are capable of doing predictive analysis and generate sample data based on given datasets.
What is the use of Data Analytics?
Business Development & Analysis using Data.
Why is Data Analysis Important?
- The fast increasing Global data, the advancement of technologies, the growth of AI and machine learning – All these make big companies make data-driven decisions. Hence, Big companies depend on data to make important financial decisions. Data Analytics is applied in Finance, Insurance, Gaming to make use of their structured and unstructured data and to make rational decisions.
- Data Analytics has become inevitable in numerous fields and is undoubtedly the most-sought-after role nowadays.
What is the Difference between Big data & Data science?
- It could be a bit confusing to differentiate between Big data and Data Science.
- Data Science is the branch of science that deals with everything about data from the cleansing, preparation, analysis of data. This is applied primarily in internet searches, Fraud detection, Digital advertisements.
- Big data refers to complex and very large data sets that are unstructured and cannot be easily handled using traditional data processing tools. It involves data storage, analysis, visualization of these data and finds the insights from them to take strategic business decisions. This is applied in Financial Services, Telecommunications, Commerce, Health and Sports.
What is a Data Scientist VS Data Analyst?
- Data Scientist works at much a deeper level compared with the data analyst.
- Data analyst just works with analyzing and querying data using simple tools like SQL, Excel and provides solutions to the business problems presented to them. Data Scientist deals with Big data (Unstructured data).
- But, Data scientist creates business questions, analyses data patterns and creates a statistical model to find answers to those questions and use visualization techniques to help others understand their findings. They solve critical business problems and make companies take strategic decisions.
What is the difference between a Data Engineer & a Data Analytics?
- Data Engineer deals with data warehouses. A data engineer is exposed to data architecture that designs, builds, works with data. A data engineer is responsible to maintain the accuracy and availability of data.
- Data Analytics, on the other hand, will develop deeper insights from the data maintained by the data engineer.
Should one be a Data Engineer or a Data Analytics?
- Data engineers usually have a programming background whereas the data Analytics comes from the mathematical background. According to Glass door, the number of jobs for Data engineers is 5 times more than the data Analytics jobs.
- Data engineer develops, constructs, maintains data. Data engineer works with tools such as MongoDB, Redis, Hive, SAP, other database tools.
- Data Analytics develops insights and solves business needs. Data Analytics uses Tableau, SAS, SPSS, Rapidminer. Both of these roles use tools such as Spark, scale, etc.
- If you have good database background and strong technical skills, go for Data Engineer role.
- If you have good analytical skills, mathematical, statistical skills along with technical expertise, You can build your career as a Data Analytics.
Key Features of Data Analytics Course
Sri Vidya Technologies offers Data Analytics Training in Chennai in more than 7+ branches with 10+ years of Experienced Expert level Trainers. Here are the key features,
Why Should I Learn Data Analytics from Sri Vidya Technologies?
- 35 Hours to 45 Hours Course Duration
- Industry Expert Faculties
- Completed 500+ Batches
- 100% Job Oriented Training
- Certification Guidance
- Learning from industry experts
- Live projects
- Real-time problems and solutions
- Flexibility
- Availability
- Connectivity with more branches
- Exam and Certification
- Placement assistance
- Mock interviews
- Frequently Asked Questions
Different Modes of Data Analytics Training
Get enrolled for the most demanding skill in the world. Data Analytics Training will make your career a new height. We at Sri Vidya technologies provide you with an excellent platform to learn and explore the subject from industry experts. We help students to dream high and achieve it. We have Data experts as our trainers. Our trainers have been working in top MNCs in good Data Analytics roles and have good experience in training students. We provide training in both classroom and online modes. We do Corporate training.
If you are a business, you sure have trust in your employees. They are efficient, no doubt. But by offering them proper data Analytics training, we will make them capable of having better insights into your company’s data. Our curriculum is comprehensive and is suitable for all kinds of employees-both from IT and non-IT backgrounds. Interestingly, our training is customization. And we facilitate customization because we acknowledge that your company is unique and its needs are also special. With customized training to your employees, we help them improve their data Analytics capabilities. And guess what! The training is imparted by excellent instructors, having industry experience. Don’t worry about time and place compatibility, we also offer online data Analytics training.
Individuals
Individual training is a training that is individualized to take into consideration the differences between learners. It is most suitably used in a one-to-one situation. Not like facilitated learning where the instructor takes a more passive role, with individual learning the trainer needs to consider and cater to the needs of individual participants. It doesn’t mean that students are at home they can be in a classroom and still work through things at their own pace.
Data Analytics Classroom Training
Group Training
We have many branches and Bangalore. In Bangalore, We have branches in Marathahalli, Jaya Nagar, Indira Nagar, BTM layout, Rajaji Nagar and Kalyan Nagar. Our branches are situated in places which have very good connectivity. We run our classes in small batch sizes which facilitates good interaction between trainer and students. Our trainers are attentive to students in case of doubts or questions in-classroom training.
One to One Training
We also provide one to one classroom training where students will be given full attention as the trainer’s time is fully dedicated to one student. Fast track classroom training: This is for students with time constraints. We give the best training at a fast pace while also covering the full syllabus as in normal classroom training.
Fast Track Training
Fast Track and flexible term courses are no different from regular semester-length courses. Sessions are more intensive, and trainees attend class more hours each week to learn. what is needed to complete the course. This type of training is for those individuals who want to complete the course quickly by taking extra hours or extra classes.
Data Analytics Online Training
Online Classroom Training
We provide online training in both one to one and batch size. This is suitable for working professionals who can grasp the subject easily but cannot travel to our branches due to time constraints.
One to One Training
One dedicated trainer for one learner, this is an excellent way of learning to understand the content in a simple way. All the Trainers are highly qualified professionals. Sri Vidya technologies are leading in 1-to-1 training, most of the learner prefers this for various benefits. Quicker learning as you get the undivided attention of the trainer. You don’t need to wait for your turn to clear your doubts. Quality of learning has an inverse relation with the number of students in a class.
Fast Track Training
Fast Track and flexible term courses are no different from regular semester-length courses. Sessions are more intensive, and trainees attend class more hours each week to learn what is needed to complete the course. This type of training is for those individuals who want to complete the course quickly by taking extra hours or extra classes.
Corporate Training
This type of training is for companies who want to train, retrain, and jointly educate employees and managers in order to grow. We love to give corporate training as we have experienced professionals who can train you at your place with excellent teaching methodologies and help to grow your company at the highest peak. We provide world-class training for corporate professionals. This is specialized and customized training based on your business requirements.
Placement Assistance after Data Analytics Training :
- Our trainers help you with each and every step in your job progress.
- Our trainers help improve your resume and help you add the necessary skills so that your resume clears the screening process.
- The live project experience gained from the class will help you in facing interview questions. Our trainers are available for you to reach out for any doubts or queries after course completion.
- We conduct mock interviews for you which boosts up your confidence level and prepares you for real-time interviews.
Data Analytics Job Opportunities
Data Analytics team comprises data analyst, data Analysis and data engineer, data architect, and so on. There is an increasing demand for data science roles and a big gap exists between the need and the availability. Hence, markets need more engineers in data Analytics jobs. The industry provides the best salary for the right candidate.
The growing demand for people who are capable of mining and interpreting data is proof enough to say that there are huge career opportunities in the field of data Analytics. And there is hardly any company that doesn’t have anything to do with data. Almost every company, irrespective of the industry in which it operates, deals with data handling. And that is why they are on a constant search for people having knowledge of data Analytics. Starting from start-ups to big players, almost every company has a requirement for experienced people. By taking a data Analytics course at Sri Vidya Technologies, you will be able to fill up job positions such as analytics manager, business analyst, business intelligence (BI) analyst, data analyst, data scientist, director of analytics, research analyst, research scientist, senior data analyst, statistician and the like. And to make sure you get the most lucrative jobs in the market, we offer placement assistance too.
What jobs can you get after completion of data Analytics course?
- You can start as a Data analyst.
- You can also get into Data Analytics or
- Data engineer positions.
- There are still more roles to explore in Data Analytics field.
What exactly does a data Analytics do?
Data Analytics deals with big data and helps organizations take strategic business decisions in solving their critical business problems.
What is a data Analysis salary?
- Start-ups pay an average salary of about 10.8 lakhs to data scientists.
- Salary can go as high up to 25 lakhs per annum.
- Tier 1 companies pay the best in the industry for data scientists.
How much do entry-level data analyst make?
Data analysts start at an average of 424,414 per year.
What are the Top Companies hiring data Analytics Professionals?
- Wipro,
- Infosys,
- Flipkart,
- Urban Ladder,
- Snapdeal,
- Amazon hires for various data science roles.
Is data science a good career option?
Data Analytics is a very good career option to step up the ladder, as it is being one of the highest-paid and niche skills of the decade. Data Analytics is the domain which has an evergreen future. A lot of companies invest good money in doing research and innovate in this field.
About Data Analytics Course
From this Data Analytics is a popular course offered by top universities & certification institutes. Data Analytics can be studied as a stand-alone program as well as under various specializations such as Business Analytics, Data Science, Big Data, Machine Learning, etc. Getting a Data Analytics certification is the most convenient way to kickstart a career in Data Analytics. Coursera, Simplilearn, edX, and Udemy are the top platforms that offer Data Analytics courses online. Candidates can also pursue an undergraduate or postgraduate degree in Data Analytics.
The eligibility criteria to pursue a post graduation or diploma course in Data Analytics is a bachelor’s degree in Business, Engineering, or Science. Candidates need to have a basic knowledge of Statistics & Mathematics. Undergraduate Data Analytics courses require students to score more than 50% marks in class 12 exams and have either Mathematics, Statistics, or Computer Science as the core subject. The article lists the best Data Analytics courses for beginners as well as experienced professionals.
Post completing a Data Analytics course, candidates can choose to pursue their career as a Data Analyst both in India as well as abroad. The average starting salary of a Data Analyst in However, with gradual experience, updated skills and knowledge the salary of a Data Analyst can go up to as much as
What are objective of our DataAntraining?
We, at Sri Vidya Technologies, provide the best training for the Data Science course. We have designed the course in such a way that helps to kick start your career into the data science field and to take up different roles such as Data Scientist, Data Engineer, Data analyst and so on.
We design the syllabus as per the latest industry standards.
- Our trainers provide real-time training with live projects which will help you to have a deeper understanding of the subject.
- We provide the training in various modes such as online, classroom on both weekday and weekend batches.
- Our training schedule is very flexible to suit your available timings.
- Our Data science course will help you to crack-related interviews in top MNCs since our trainers will guide you throughout the process by sharing their real-time experience in relevant fields.
What is Data Analytics?
- As the process of analyzing raw data to find trends and answer questions, the definition of data analytics captures its broad scope of the field. However, it includes many techniques with many different goals.
The data analytics process has some components that can help a variety of initiatives. By combining these components, a successful data analytics initiative will provide a clear picture of where you are, where you have been and where you should go.
Why Should you go for Data Analytics Training?
If you want to succeed in this digital world that is creating a knowledge-based society, you must study trends. Right from MN C’s to start-ups, everyone depends on data to formulate improved strategies for the future of their companies.
1. Data analytics is significant for top organisations
The outburst of data is transforming businesses. Companies – big or small – are now expecting their business decisions to be based on data-led insight. Data specialists have a tremendous impact on business strategies and marketing tactics.
2. Job opportunities on the rise
The Science and Technology Committee published this report and noted that 58,000 jobs could be created and £216bn contributed to our economy (2.3% of GDP) by 2021.
The demand for data specialists is on the rise while the supply remains low, thus creating great job opportunities for individuals within this field.
Today, it is almost impossible to find any brand that does not have social media presence; soon, every company will need data analytics professionals. This makes it a wise career move that has a future in business.
3. Increasing salaries for data analytics professionals
According to Prospects, entry level salaries for data analytics professionals range between £24,000 and £25,000. With a few years’ experience, salaries can rise to somewhere between £30,000 and £35,000, while high-level professionals and consultants may earn £60,000 or more.
4. Work opportunities in a spectrum of industries
Many industries are reliant on data, so you could opt for a career in any number of industries, including:
- business intelligence
- marketing
- sales
- finance
- data assurance
- data quality
- higher education
5. You will influence the decision-making in the company
While most company employees feel the lack of decision-making power causing job dissatisfaction, that’s not the case for data professionals.
With a unique role within the company, you will be a vital part of business policies and future strategies thus making it a very rewarding career.
6. It presents perfect freelancing opportunities
Data analytics is also a prospect to become a well-paid consultant for some of the major firms in the world. As the job is mainly IT based, with a good internet connection, it can be done from any part of the world. This gives you the perfect opportunity to broaden your sources of income and provide yourself with a good work-life balance.
Browse our data analytics courses to become a vital professional of one of the biggest in-demand careers.
What is the Role of Data Analytics?
Data analysts exist at the intersection of information technology, statistics and business. They combine these fields in order to help businesses and organizations succeed. The primary goal of a data analyst is to increase efficiency and improve performance by discovering patterns in data.
How will Data Analytics Training help your Career?
- Since top companies don’t usually prefer freshers for these roles, experience in real-time Data Analytics projects will be an added advantage.
- Our training is focused on covering all basic syllabus related to Data Analytics along with real-time Lab exercises. Our live projects will help you to understand the subject in an extensive way and prepare you to face interviews with top companies for Data Analytics roles.
- Our trainers will share with you their experience and guide you to solve real-time problems. Either Online or classroom training is mandatory to start a career in Data Analytics.
what are prerequisites for Data Analytics Training?
If you are looking for a career in data analytics, I would suggest that you take up a job in one of the analytics companies – Mu Sigma, ZS associates, Fractal, Credence, etc. These companies mostly don’t need any prerequisites for entry level analyst jobs and provide great opportunities to learn the skills from scratch
If that’s not possible for you, I would suggest you take the following progression to learn data analytics in each of the key areas:
Mathis
- Basic statistics and data summarizing parameters like mean, median, mode, central tendencies, distributions, etc.
- Data integrity, comparison and tendency tests like t-test, z-test, f-test
- Regression – Linear, Logistic, GLM, Mixed in that order
- Advanced techniques like predictive modeling and prescriptive methods
Technology
- Microsoft Excel: This is the Holy grail of analytics. Learn this in and out. From simple formulae to the data analytics tool and dashboard in, you should learn it all
- VBA: This is an extension of Excel and though not used very extensively, can help in making a lot of tasks in excel easier
- SQL: This is the logical progression from Excel for handling larger data volumes and also standardizing processes and creating code modules for repeated use
- SAS/R: The next step will be one of these tools as they can help you do more complex processing like regression and modeling
- Tableau: This is almost the standard right now for data visualization and dashboarding
- Advanced technologies like Shiny, Hadoop, Hive, etc
What Skills will you learn in Data Analytics Training?
To prepare for a new career in the high-growth field of data analysis, start by developing these skills.
7 In-Demand Data Analyst Skills to Get You Hired in 2022
- SQL. …
- Statistical programming. …
- Machine learning. …
- Probability and statistics. …
- Data management. …
- Statistical visualization. …
- Econometrics.
The following are the skills that are associated with data Analytics.
Each year, there is more demand for data analysts and scientists than there are people with the right skills to fill those roles In fact, according the US Bureau of Labor Statistics the number of job openings for analysts is expected to grow by 23-percent between 2021 and 2031, significantly higher than the five percent average job growth projected for all jobs in the country
Prerequisites to Learn Data Analytics course
Over the years, data science has become an essential part of every business. It solves many problems within a given field through data analysis and interpretation of various data. There are few online resources stating that the candidate needs to be skilled in database query languages, software development, mathematics, programming visualization station, statics the etc as a basic requirement to become a data scientist.
This might discourage the beginners, who enter dreaming of becoming a Data Scientist. There are few institutes like Sri Vidya technologies that offer specialized programs, tailored to the educational requirements to pursue a career in data science. However, the skills aren’t mandatory for a beginner, as there are many MOOCs that will help one to learn those required skills. Also, many senior data scientists have mentioned that Data Scientist is a blanket job with varied types of data and skills. These skills need to be developed over time in order to match the available data science job.Though there is too much confusion, still the questions might vary from every person based on their individual needs and qualification. To get clarity on this, here is the answer to a set of few questions with the both technical and non-technical disciplines that arise with the candidate.
Technical skills
- Ph.D. or Masters a necessary
- Math or Statistics compulsory
- Hard-core programmer
- SQL and Hadoop skills
- Data Analytics degree
- Machine learning concepts
Is Master’s or Ph.D. is necessary?
A Masters degree or a Ph.D. in data Analytics is required for professionals who need to place themselves in the top positions with some good years of experience. But it is not required for a beginner and also there is a number of possible ways available today to learn data science for working professionals even which are flexible yet valuable. The real Data Analytics experience is gained by the real time experience gained in addition to the course. But still, expertise with a Ph.D. can always prove with their knowledge and be in the top positions. This scenario is very true with Google, as they recruit only the Ph.D. or Masters degree holders for Data Analytics positions.
Is a degree in Math or Statistics is needed?
People from diverse backgrounds like economics, operations research, statistics, computer science, mathematics etc are practicing as the data scientist. This is because, being familiar with the basic concepts of statistics and maths with linear algebra, probability, calculus etc is essential to understand data science.
Are SQL and Hadoop necessary?
SQL language fundamentals in creating indexes, group by, joins etc is necessary to understand data science. Also, the basic SQL knowledge will help in understanding the Hadoop cluster. The emerging technologies like Map Reduce, Hive, and Pig etc will be easy for SQL and HADOOP programmers to learn.
What is the Educational Qualification for Data Analytics?
Other than certification or diploma courses, Data Analytics is also available at the postgraduate level as a stream of specialization in Computer Science and Management. The minimum eligibility criteria for a postgraduate Data Analytics course is a Bachelor’s degree with at least 50% marks in aggregate or equivalent preferably in Science or Computer Science from a recognized university.. Today, technology is helping us to learn all these courses through MOOC from wherever we are. But still learning these courses will not be helpful in learning the soft skills and managing skills required for data scientist job.
Data Analytics Course
Although there are many IT training institutes , you cannot take a data Analytics course from any random institute. For desired results, you need to enroll yourself with Sri Vidya Technologies, the best institute offering Data Analytics training . Sri Vidya Technologies offers Best Data Analytics Training Courses in Velachery, Tambaram, OMR, Porur, Anna Nagar, T-Nagar, Adyar and Thiruvanmiyur . We teach students everything that is important- starting from basic to advanced concepts, that too in a real-time environment.
Data Analytics training with Advanced SAS: Macros & SQL
Advanced SAS that covers both Macros and SQL has huge varieties of statistical functions. Although there are many tools that help with data science, SAS has special significance not just in the field of data science but also advanced analytics. Throughout its rule in the market, it has been superbly adaptable and plastic. Reading data from all kinds of databases is possible with SAS. Tasks like processing of data on the RAM get easily pulled off by SAS. The probability of distribution of data and complex simulations have always been easy with SAS. You will be glad to know that we, at Sri Vidya, teach all the nitty-gritty involved in using SAS Advanced: Macros and SQL in the field of data science.
SQL
Structured Query Language, or SQL, is the standard language used to communicate with databases. Knowing SQL lets you update, organize, and query data stored in relational databases, as well as modify data structures (schema).
Since almost all data analysts will need to use SQL to access data from a company’s database, it’s arguably the most important skill to learn to get a job. In fact, it’s common for data analyst interviews to include a technical screening with SQL.
Luckily, SQL is one of the easier languages to learn.
Get fluent in SQL: Develop SQL fluency, even if you have no previous coding experience, with the Learn SQL Basics for Data Science Specialization from CU Davis. Work through four progressive SQL projects as you learn how to analyze and explore data.
Statistical programming
Statistical programming languages, like R or Python, enable you to perform advanced analyses in ways that Excel cannot. Being able to write programs in these languages means that you can clean, analyze, and visualize large data sets more efficiently.
Both languages are open source, and it’s a good idea to learn at least one of them. There’s some debate over which language is better for data analysis. Either language can accomplish similar data science tasks. While R was designed specifically for analytics, Python is the more popular of the two and tends to be an easier language to learn (especially if it’s your first).
Learn your first programming language: If you’ve never written code before, Python for Everybody from the University of Michigan is a good place to start. After writing your first simple program, you can start to build more complex programs used to collect, clean, analyze, and visualize data.
3. Machine learning
Machine learning, a branch of artificial intelligence (AI), has become one of the most important developments in data science. This skill focuses on building algorithms designed to find patterns in big data sets, improving their accuracy over time.
The more data a machine learning algorithm processes, the “smarter” it becomes, allowing for more accurate predictions.
Data analysts aren’t generally expected to have a mastery of machine learning. But developing your machine learning skills could give you a competitive advantage and set you on a course for a future career as a data scientist.
Get started in machine learning: Andrew N’s Machine Learning Specialization from Stanford is one of the most highly-rated courses on Coursers. Learn about the best machine learning techniques and how to apply them to problems in this introductory class.
Data Analytics : About Trainer
Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.
- More than 7+ Years of Experience.
- Trained more than 2000+ students in a year.
- Strong Theoretical & Practical Knowledge.
- Certified Professionals with High Grade.
- Well connected with Hiring HRs in multinational companies.
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
- Trainers have Experienced on multiple real-time projects in their Industries.
- Our Trainers are working in multinational companies such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc
Trainer Profile of Data Analytics Course
We choose the best trainers for you. The best thing about taking Data Analytics Training at Sri Vidya Technologies is certainly the trainers here. They are the best you can avail of and will take care of all your academic needs. The best thing about the approach with which they impart training to the candidates is that its student-centric. That means the training imparted to you is based on your needs, demands and comfort level. The teachers do their best to make sure their knowledge and wisdom in the field of data science get effortlessly passed on to you. They don’t just have immense theoretical knowledge but also a lot of practical experience to enrich you with.
- Our trainers are industry data experts who work in Data Analytics.
- Most of our trainers work in companies and have considerable work experience in Data Analytics field.
- Our trainers are flexible and are available based on your timings
- Our trainers have good experience in training and are good at demonstrating the solution for real-world data Analytics problems.
Key Features of Data Science Training
Introduction to Data Analytics
This course presents a gentle introduction into the concepts of data analysis, the role of a Data Analyst, and the tools that are used to perform daily functions. You will gain an understanding of the data ecosystem and the fundamentals of data analysis, such as data gathering or data mining. You will then learn the soft skills that are required to effectively communicate your data to stakeholders, and how mastering these skills can give you the option to become a data driven decision maker.
This course will help you to differentiate between the roles of a Data Analyst, Data Scientist, and Data Engineer. You will learn the responsibilities of a Data Analyst and exactly what data analysis entails. You will be able to summarize the data ecosystem, such as databases and data warehouses. You will then uncover the major vendors within the data ecosystem and explore the various tools on-premise and in the cloud. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you will be able to visualize the daily life of a Data Analyst, understand the different career paths that are available for data analytics, and identify the many resources available for mastering this profession.
This course is part of multiple programs
- IBM Data Analytics with Excel and R Professional Certificate
- IBM & Darden Digital Strategy Specialization
- Data Analysis and Visualization Foundations Specialization
- IBM Data Analyst Professional Certificate
What is Data Analytics?
The field of data science is interdisciplinary, which encompasses a lot of areas including scientific methods, processes, systems, and algorithms. This field is deeply connected with big data and analytics. With proper training in data science, you make yourself eligible for recruitment in a lot of companies that have data handling jobs available with them. The world has been taken over by big data. And with the foothold of big data growth in the world, the need for its storage began to grow. Enterprise industries saw it as a challenge till somewhere around 2010. At that time, more emphasis was being laid on building solutions and frameworks for the storage of data. Then came frameworks like Hadoop that indeed solved the problem of data storage.
But then a new problem arose- processing of this stored data. Here comes the role of data science. In Hollywood sci-fi movies, you see a lot of seemingly unrealistic ideas. Believe it or not, all such ideas can be turned into reality with the help of data science. In another way, you can say that the future of artificial intelligence lies in data science. And that is probably the reason why data science and its courses are so much in demand. People want to learn it for lucrative IT career options. So, data science, which is a concoction of machine learning principles, algorithms, and various tools, is used to figure out concealed patterns in raw data. It is because of data science that data can be used to add value to any business. Predictive causal analytics, prescriptive analytics, and machine learning are the elements that together render data science helpful in making decisions and predictions. Here, it would be valuable to add that the future lies in the hands of data scientists. The need for data scientists that have expertise over the subject is growing with each passing day. What more? Well, data science is changing the way people look at the world flooded with data.
What skills are needed to be a Data Analytics?
- A data scientist Analytics should be an expert in multiple skills such as Mathematics, statistics, Big Data.
- Data Analysis should have a deeper understanding of Mathematics, Statistics and should have good analytical skills to understand patterns in these data.
- We should be able to develop machine learning algorithms that are capable of doing predictive analysis and generate sample data based on given datasets.
What is the use of Data Analytics?
Business Development & Analysis using Data.
Why is Data Analysis Important?
- The fast increasing Global data, the advancement of technologies, the growth of AI and machine learning – All these make big companies make data-driven decisions. Hence, Big companies depend on data to make important financial decisions. Data Analytics is applied in Finance, Insurance, Gaming to make use of their structured and unstructured data and to make rational decisions.
- Data Analytics has become inevitable in numerous fields and is undoubtedly the most-sought-after role nowadays.
What is the Difference between Big data & Data science?
- It could be a bit confusing to differentiate between Big data and Data Science.
- Data Science is the branch of science that deals with everything about data from the cleansing, preparation, analysis of data. This is applied primarily in internet searches, Fraud detection, Digital advertisements.
- Big data refers to complex and very large data sets that are unstructured and cannot be easily handled using traditional data processing tools. It involves data storage, analysis, visualization of these data and finds the insights from them to take strategic business decisions. This is applied in Financial Services, Telecommunications, Commerce, Health and Sports.
What is a Data Scientist VS Data Analyst?
- Data Scientist works at much a deeper level compared with the data analyst.
- Data analyst just works with analyzing and querying data using simple tools like SQL, Excel and provides solutions to the business problems presented to them. Data Scientist deals with Big data (Unstructured data).
- But, Data scientist creates business questions, analyses data patterns and creates a statistical model to find answers to those questions and use visualization techniques to help others understand their findings. They solve critical business problems and make companies take strategic decisions.
What is the difference between a Data Engineer & a Data Analytics?
- Data Engineer deals with data warehouses. A data engineer is exposed to data architecture that designs, builds, works with data. A data engineer is responsible to maintain the accuracy and availability of data.
- Data Analytics, on the other hand, will develop deeper insights from the data maintained by the data engineer.
Should one be a Data Engineer or a Data Analytics?
- Data engineers usually have a programming background whereas the data Analytics comes from the mathematical background. According to Glass door, the number of jobs for Data engineers is 5 times more than the data Analytics jobs.
- Data engineer develops, constructs, maintains data. Data engineer works with tools such as MongoDB, Redis, Hive, SAP, other database tools.
- Data Analytics develops insights and solves business needs. Data Analytics uses Tableau, SAS, SPSS, Rapidminer. Both of these roles use tools such as Spark, scale, etc.
- If you have good database background and strong technical skills, go for Data Engineer role.
- If you have good analytical skills, mathematical, statistical skills along with technical expertise, You can build your career as a Data Analytics.
Key Features of Data Analytics Course
Sri Vidya Technologies offers Data Analytics Training in Chennai in more than 7+ branches with 10+ years of Experienced Expert level Trainers. Here are the key features,
Why Should I Learn Data Analytics from Sri Vidya Technologies?
- 35 Hours to 45 Hours Course Duration
- Industry Expert Faculties
- Completed 500+ Batches
- 100% Job Oriented Training
- Certification Guidance
- Learning from industry experts
- Live projects
- Real-time problems and solutions
- Flexibility
- Availability
- Connectivity with more branches
- Exam and Certification
- Placement assistance
- Mock interviews
- Frequently Asked Questions
Different Modes of Data Analytics Training
Get enrolled for the most demanding skill in the world. Data Analytics Training will make your career a new height. We at Sri Vidya technologies provide you with an excellent platform to learn and explore the subject from industry experts. We help students to dream high and achieve it. We have Data experts as our trainers. Our trainers have been working in top MNCs in good Data Analytics roles and have good experience in training students. We provide training in both classroom and online modes. We do Corporate training.
If you are a business, you sure have trust in your employees. They are efficient, no doubt. But by offering them proper data Analytics training, we will make them capable of having better insights into your company’s data. Our curriculum is comprehensive and is suitable for all kinds of employees-both from IT and non-IT backgrounds. Interestingly, our training is customization. And we facilitate customization because we acknowledge that your company is unique and its needs are also special. With customized training to your employees, we help them improve their data Analytics capabilities. And guess what! The training is imparted by excellent instructors, having industry experience. Don’t worry about time and place compatibility, we also offer online data Analytics training.
Individuals
Individual training is a training that is individualized to take into consideration the differences between learners. It is most suitably used in a one-to-one situation. Not like facilitated learning where the instructor takes a more passive role, with individual learning the trainer needs to consider and cater to the needs of individual participants. It doesn’t mean that students are at home they can be in a classroom and still work through things at their own pace.
Data Analytics Classroom Training
Group Training
We have many branches and Bangalore. In Bangalore, We have branches in Marathahalli, Jaya Nagar, Indira Nagar, BTM layout, Rajaji Nagar and Kalyan Nagar. Our branches are situated in places which have very good connectivity. We run our classes in small batch sizes which facilitates good interaction between trainer and students. Our trainers are attentive to students in case of doubts or questions in-classroom training.
One to One Training
We also provide one to one classroom training where students will be given full attention as the trainer’s time is fully dedicated to one student. Fast track classroom training: This is for students with time constraints. We give the best training at a fast pace while also covering the full syllabus as in normal classroom training.
Fast Track Training
Fast Track and flexible term courses are no different from regular semester-length courses. Sessions are more intensive, and trainees attend class more hours each week to learn. what is needed to complete the course. This type of training is for those individuals who want to complete the course quickly by taking extra hours or extra classes.
Data Analytics Online Training
Online Classroom Training
We provide online training in both one to one and batch size. This is suitable for working professionals who can grasp the subject easily but cannot travel to our branches due to time constraints.
One to One Training
One dedicated trainer for one learner, this is an excellent way of learning to understand the content in a simple way. All the Trainers are highly qualified professionals. Sri Vidya technologies are leading in 1-to-1 training, most of the learner prefers this for various benefits. Quicker learning as you get the undivided attention of the trainer. You don’t need to wait for your turn to clear your doubts. Quality of learning has an inverse relation with the number of students in a class.
Fast Track Training
Fast Track and flexible term courses are no different from regular semester-length courses. Sessions are more intensive, and trainees attend class more hours each week to learn what is needed to complete the course. This type of training is for those individuals who want to complete the course quickly by taking extra hours or extra classes.
Corporate Training
This type of training is for companies who want to train, retrain, and jointly educate employees and managers in order to grow. We love to give corporate training as we have experienced professionals who can train you at your place with excellent teaching methodologies and help to grow your company at the highest peak. We provide world-class training for corporate professionals. This is specialized and customized training based on your business requirements.
Placement Assistance after Data Analytics Training :
- Our trainers help you with each and every step in your job progress.
- Our trainers help improve your resume and help you add the necessary skills so that your resume clears the screening process.
- The live project experience gained from the class will help you in facing interview questions. Our trainers are available for you to reach out for any doubts or queries after course completion.
- We conduct mock interviews for you which boosts up your confidence level and prepares you for real-time interviews.
Data Analytics Job Opportunities
Data Analytics team comprises data analyst, data Analysis and data engineer, data architect, and so on. There is an increasing demand for data science roles and a big gap exists between the need and the availability. Hence, markets need more engineers in data Analytics jobs. The industry provides the best salary for the right candidate.
The growing demand for people who are capable of mining and interpreting data is proof enough to say that there are huge career opportunities in the field of data Analytics. And there is hardly any company that doesn’t have anything to do with data. Almost every company, irrespective of the industry in which it operates, deals with data handling. And that is why they are on a constant search for people having knowledge of data Analytics. Starting from start-ups to big players, almost every company has a requirement for experienced people. By taking a data Analytics course at Sri Vidya Technologies, you will be able to fill up job positions such as analytics manager, business analyst, business intelligence (BI) analyst, data analyst, data scientist, director of analytics, research analyst, research scientist, senior data analyst, statistician and the like. And to make sure you get the most lucrative jobs in the market, we offer placement assistance too.
What jobs can you get after completion of data Analytics course?
- You can start as a Data analyst.
- You can also get into Data Analytics or
- Data engineer positions.
- There are still more roles to explore in Data Analytics field.
What exactly does a data Analytics do?
Data Analytics deals with big data and helps organizations take strategic business decisions in solving their critical business problems.
What is a data Analysis salary?
- Start-ups pay an average salary of about 10.8 lakhs to data scientists.
- Salary can go as high up to 25 lakhs per annum.
- Tier 1 companies pay the best in the industry for data scientists.
How much do entry-level data analyst make?
Data analysts start at an average of 424,414 per year.
What are the Top Companies hiring data Analytics Professionals?
- Wipro,
- Infosys,
- Flipkart,
- Urban Ladder,
- Snapdeal,
- Amazon hires for various data science roles.
Is data science a good career option?
Data Analytics is a very good career option to step up the ladder, as it is being one of the highest-paid and niche skills of the decade. Data Analytics is the domain which has an evergreen future. A lot of companies invest good money in doing research and innovate in this field.