Career opportunities as Data Analyst

In the era of Information and Technology, the role of Data analysts has become critical to cope with the present needs of the consumers and companies. Data analysts collect process and perform statistical analyses of data. Their skills may not be as advanced as data scientists (e.g. they may not be able to create new algorithms), but their goals are the same – to discover how data can be used to answer questions and solve problems.

Responsibilities
• Work with IT teams, management and/or data scientists to determine organizational goals
• Mine data from primary and secondary sources
• Clean and prune data to discard irrelevant information
• Analyze and interpret results using standard statistical tools and techniques
• Pinpoint trends, correlations and patterns in complicated data sets
• Identify new opportunities for process improvement
• Provide concise data reports and clear data visualizations for management
• Design, create and maintain relational databases and data systems
• Triage code problems and data-related issues

Data analysts are sometimes called “junior data scientists” or “data scientists in training.” Instead of being free to create their own big data projects, they may be limited to tackling specific business tasks using existing tools, systems and data sets. However, there are plenty of companies who don’t make a clear distinction between the two roles. In some cases, a data analyst/scientist could be writing queries or addressing standard requests in the morning and building custom solutions or experimenting with relational databases, Hadoop and NoSQL in the afternoon.

Qualifications
Most candidates for entry-level jobs will need a bachelor’s degree in math, statistics computer science, information management, finance or economics. All of these subjects place a heavy emphasis on statistical and analytical skills. To climb the career ladder or transition to the role of a data scientist, you will probably be required to earn a master’s degree or graduate certificate in a similar field.

Technical skills
• Statistical methods and packages (e.g. SPSS)
• R and/or SAS languages
• Data warehousing and business intelligence platforms
• SQL databases and database querying languages
• Programming (e.g. XML, Javascript or ETL frameworks)
• Database design
• Data mining
• Data cleaning and munging
• Data visualization and reporting techniques
• Working knowledge of Hadoop & MapReduce
• Machine learning techniques.

Business skills
• Analytic Problem-Solving: Employing best practices to analyze large amounts of data while maintaining intense attention to detail.
• Effective Communication: Using reports and presentations to explain complex technical ideas and methods to an audience of laymen.
• Creative Thinking: Questioning established business practices and brainstorming new approaches to data analysis.
• Industry Knowledge: Understanding what drives your chosen industry and how data can contribute to the success of a company/organization strategy.

Similar Jobs
In many cases, Market Research Analysts, Quantitative Analysts, Operations Analysts and similar field-specific positions can be found under its shade. You’ll also see a good deal of job crossover with Business Intelligence Analysts, Data Warehouse Analysts and Business Systems Analysts.

Senior data analysts are close siblings to Data Scientists and Analytics Managers. At the upper levels of management, there may be no clear distinction between the 3 roles.

Analysts who grow tired of analyzing may wish to investigate data construction jobs such as:
• Data/Big Data Engineer
• Data/Big Data Architect

Job outlook
Today’s data analysts should be prepared for a change. Self-service business intelligence software and automation is replacing many of the regular tasks that – in the past – technical experts would have been required to handle.

Data analysts monitor KPIs, build dashboards, generate data reports and identify business strengths and weaknesses by themselves. The need for analysts to extract structured information from databases and prepare it for consumption is rapidly decreasing.

On the other hand, the need for statistical gurus to handle the flood of unstructured data is rapidly increasing. These men and women are obliged to clean, filter and convert billions of diverse data points.

They must employ complex modeling and predictive analytics techniques to generate useful insights and actions. Then they have to explain what they’ve discovered to rooms of confused laymen. In other words, they have to transform themselves from data analysts into data scientists.

Salaries
The Salary of Data analysts depends on job responsibilities. A senior data analyst with the skills of a data scientist can command a high price. An entry-level data analyst with basic technical tools might be looking at anything from Rs. 12 lakhs to 16 lakhs per year.
According to Pay Scale, the best-paying jobs in 2016 the median pay for analysts were Rs.40 lakhs (25% above the national average).

Helpful organisations
• Data Management Association International (DAMA)
• Data Science Association
• Digital Analytics Association (DAA)
• International Institute for Analytics (IIA)
• International Machine Learning Society (IMLS)
• Institute for Operations Research and the Management Sciences (INFORMS)
• SIGKDD

Gudipati Rajendera Kumar