Best Data Analyst Course in India | NIIT Digital

3 Key Skills Every Data Analyst Needs Now

The importance of a data analyst's work has grown in the modern, data-driven society. Companies are increasingly relying on data analysts to help them make better choices by gleaning insights from raw data. A data analyst has both technical knowledge and people skills to succeed in an ever-changing industry.

Table of Contents:

• The 3 Key Skills for Data Analysts
• The Most Useful Upskilling Programs
• Conclusion

The Three Key Skills for Data Analysts

1. Statistical Knowledge

Data analysts must have a solid grasp of statistical principles. This requires familiarity with probability theory, inferential statistics (such as hypothesis testing and regression analysis), and descriptive statistics (such as mode, median, and mean). If you want to get to the bottom of data and make smart judgements, statistical analysis is your tool.

2. Programming Skills

Data analysts must be proficient in SQL, Python, or R, among others. Data analysis, visualization, and manipulation are prominent uses for these languages. Python and R have gained immense popularity due to their vast libraries and tools that are designed to assist with data analysis.

3. Data Cleaning and Wrangling

Before data can be analyzed, it must first be cleaned and organized. Managing outliers, missing values, data type transformations, and dataset mergers are all part of this process. Data cleaning and manipulation skills are highly valued when working with tools like Pandas or Dplyr.

The Most Useful Upskilling Programs

Owing to a surge in demand for skilled data analysts, several leading institutes are offering comprehensive data analyst courses in India to meet this requirement. Some prominent institutes providing data analyst course in India include:

1. Data Analytics Program with Generative AI from NIIT

The Data Analytics Program with Generative AI from NIIT is a comprehensive 16-32 week program with a generative AI edge. It is designed for learners who want to master the core data analytics skills and learn the latest technology of generative AI.

The program covers topics such as:

• Analyse and visualize data using Excel
• Use SQL to work with RDBMS
• Python programming
• Data Analytics using Python libraries
• Exploratory Data Analysis (EDA)
• Visualize data using Tableau
• EDA using Tableau
• Capstone project

The program also provides learners with industry and career support, such as:

• Industry Projects
• Mentorship and Guidance from Experts
• Certification and Accreditation from NIIT and StackRoute
• Job Assistance and Placement Support

The data analytics certification program is delivered online, with mentor-led sessions, interactive activities, and real-world projects. The program also provides NIIT certification and placement assistance for successful graduates.

2. Post Graduate Program in Data Science and Business Analytics by Great Learning

A Postgraduate Programme in Data Science and Business Analytics is available via Great Learning in partnership with leading academic institutions and professionals in the field.  

Some of the topics covered include:

• Statistics and Exploratory Data Analysis
• Machine Learning and Predictive Analytics
• Big Data Technologies (Hadoop, Spark)
• Data Visualization with Tableau and Power BI
• Python and R Programming for Data Science
• Time Series Analysis and Forecasting
• Natural Language Processing (NLP)
• Capstone Project and Case Studies

Students collaborate with experienced instructors on projects related to their majors. Great Learning certification and career support services like networking events and job assistance are awarded to graduates.

Conclusion

Technical knowledge, strong communication skills, and the ability to solve complex problems are all essential components of a well-rounded skill set for a data analyst. In today's data-driven world, data analysts may have a big impact on their companies' performance by acquiring and honing five essential skills. 

Data analysts will be able to overcome the challenges they face and realize data's full potential if they are dedicated to learning and constantly improving their abilities.

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