Data Analytics Career

Data Analytics Certification: How it can help you build a successful career as a Data Analyst

NIIT Editorial Thu, 17/09/2020 - 13:00

 

Data analytics is a relatively new technology with wide applications. You can find a large number of students opting for data analytics training and certification. Organizations, too, stress on a data analytics certification if you are trying for a job as an analyst. 

But, what is data analytics? What does a Data Analyst do? And how a data analytics certification can help build a successful career as a Data Analyst? Today we’ll answer such questions.

What do Data Analysts do?

 

A Data Analyst job entails using a data-driven approach to solve business problems and optimizing business processes. Data Analysts use data in multiple forms, and from various sources and look for patterns and trends in that data using advanced analytical tools. They then analyze and report this data in a way that is understandable by the project stakeholders.

What are the types of data analytics?

 

There are four major types of data analytics-

  • Descriptive data analytics

This type of data analytics is used to assess what happened in the past and the factors that might have influenced it. It involves sifting through data sets that have already been aggregated for trends and patterns. Examples of this include monthly revenue reports and KPI dashboards.

  • Diagnostic data analytics

This type of data analytics builds on descriptive data analytics to find out the cause. It involves making more connections between the data and identifying the patterns of behavior. Examples include checking why a particular product performed well in the last quarter and which marketing activities proved to be most effective.

  • Predictive data analytics

Predictive analytics uses the data gathered and the insights from the previous steps to predict the future trend. It relies on statistical modelling. The accuracy of the prediction is proportional to the quality of the data. Examples include sales forecasts and risk assessment.

  • Prescriptive data analytics

Prescriptive data analytics combines insights from all the aforementioned types of data analytics to chart a future course of action and solve business problems. It is the most advanced type and requires extensive manpower and technology. Examples include AI systems used for decision making.

 

What are the responsibilities of a Data Analyst?

 

A Data Analyst’s roles and responsibilities can be diverse and varied depending on the company and the field. Here are some of the basic job responsibilities of a Data Analyst-

- The Data Analyst is responsible for collecting data from multiple sources. This step also involves checking for discrepancies and cleaning the data and making it ready to be processed by the machine.

- Data Analysts use data analytics tools to process and analyze data and identify patterns and trends. They even leverage this data to find answers to a particular business problem.

- Reporting is an integral part of a Data Analyst’s job. They have to convert results into diagrams, graphs, charts, maps, and other visual representations to ensure that all the stakeholders easily understand it.

- They also need to collaborate with engineers and developers and the business teams to understand the problem and use their data analytics skills to solve it.

For performing these functions effectively, a Data Analyst needs to have specific skills. If you are looking to become a Data Analyst, you would need to polish the skills given below.

 

What are the skills that you need for a Data Analyst job?

 

Here are some of the skills required for a data analyst.

  • Analytics skills

Analytics skills form the core of a Data Analyst’s job. You need to collect data, analyze it, and then present it in a form that can be understood by the stakeholders. Many software packages can help you with this. But a basic understanding of how these software packages work is one of the key skills for a Data Analyst.

  • Communication Skill

Communication skills are important in every field, but they are all the more critical when it comes to data analytics. You must have excellent listening, speaking, and reading skills to understand the problem and explain the solution. You need to collaborate with your colleagues, professionals from fields different than yours, and other stakeholders. Thus, your communication needs to be as clear as possible.

  • Critical Thinking

It is one of the essential Data Analyst skills. To find a solution to a problem, you must know the right questions to ask. Even though this is an innate quality, you can build on it, by staying clear about your goal and keeping the basic questions in mind as you go about finding a solution. Remember, not to make a problem more complicated than it already is.

  • Attention to Details

Data analytics involves coding and using other tools. It requires a significant amount of focus. A small syntactical error can cause errors and disrupt the entire program. Hence, you need to pay attention to detail when you are coding.

  • Math Skills

Data analytics tools use probability and statistics for solving business problems. Even though there are advanced computational tools built for the very purpose, you should be acquainted with the necessary math skills. From solving basic arithmetic problems to advanced logical operations you must know it all.

  • Technical Skill/Tools

Technical skills in data analytics are also an essential part of working as a Data Analyst. You must be aware of the basic tools like Pivot tables in Excel and fundamental Python programs. Read on to know about the tools which a Data Analyst uses, that you can learn.

 

What tools do Data Analysts use?

 

There are several tools and business intelligence software packages that a Data Analyst uses for sourcing and processing the data and reporting it. Many organizations have their proprietary tools for data analytics. However, there are some basic data analytics tools, which are commonly used. We list some of the most popular ones-

  • MS Excel

Excel is one of the most widely used tools for data analytics and reporting. Most of the companies use Excel spreadsheets to store their data. Many advanced analytics tools also use raw data in a spreadsheet format for processing. You can use formulae, pivot tables, macros, and logical operators to process data in Excel. You can also present data using dashboards, charts, and graphs.

  • Python

It is an open-sourced object-oriented programming language which is easy to use, on account of its similarity to other languages such as Javascript and PHP. It supports functional, as well as structural programming. It has excellent machine learning libraries like Tensorflow and Keras, which add to its usability. 

  • R Programming

One of the most commonly used tools in data analytics, it is incredibly helpful in data modelling. It is preferred for the amount of data that it can handle, delivering both performance and results. R can be compiled and run on a wide range of commonly used operating systems like Windows, UNIX, and macOS, as well.  

  • SAS

A leader in analytics, SAS is one of the leading programming environments and data manipulation tools in use since 1966. It has multiple modules that can be used for websites, social media, and marketing analytics. It can help in consumer profiling and widening your customer base. It can also assist in predicting market behavior, and be used to reach out to your customers.

  • Tableau Public

An open-source software package, Tableau Public is one of the best data visualization tools in the market. It is compatible with a multitude of data sources and can help in creating data maps and dashboards, with real-time updates. It can also be shared with your client in a wide range of file formats. Its Big Data capabilities further add to the usefulness. This makes Tableau one of the most important tools in data analytics.

Data analytics is finding applications in every sector. As a result, data analytics skills are in demand. This makes a data analytics certification highly coveted. You can use it to apply for a job as a fresher or to advance in your current job role and become a senior data analyst.

NIIT offers extensive courses in data analytics like Data Analytics and Visualization in Excel and Power BI, Programming in R, and Python Programming and Data Exploration in Python. Taught by expert teachers who have vast experience across a variety of sectors, these are amongst the best data analytics courses in India. Backed by intensive hands-on training, these courses make you industry-ready and fully equipped to work as a Data Analyst.

 

subscription for newsletter

Please tick this box to indicate that you understand that your personal data will be used in accordance with the Privacy Policy here. *