What is Data Analytics – Know its Types, Applications and Career Opportunities

What is Data Analytics – Know its Types, Applications and Career Opportunities | Data Analytics | Emeritus

Data is at the core of everything today. But merely having volumes of data without technology that can help in utilizing it to derive meaningful outcomes is not enough. This is where the need for data analysis arises.

Extracting information from the data available can help in empowering individuals and organizations to make better decisions. From personalizing customer interactions, predicting future health needs to creating the next big entertainment platform, data analysis has multifarious use cases. Let’s understand what data analytics is and what are the prospects for those who take up courses in the times ahead.

What is Data Analytics?

The answer to the question ‘what is data analytics’ is very straightforward. It is the process of analysing chunks of raw data to derive meaningful and actionable insights. It is a form of business intelligence which helps in solving specific problems and challenges.

For instance, through data analytics, an e-commerce company can track customer behaviour and use the insights to improve the entire experience. Data analytics tools help in contemplating past trends and predicting future ones, facilitating better and more informed choices that are not based on random guesswork.

  • Identifying the problem area
  • Collection of raw data sets that can help resolve the problem
  • Cleaning the data for analysis including duplicate records
  • Analysing the data through data analytics tools
  • Interpreting the results, finding patterns and improving on the results

Different Types of Data Analytics

We’ve put together four different types of data analytics,

  • Descriptive This surface-level analysis is aimed at analysing past data through data aggregation and data mining.
  • Diagnostic This kind of analysis explores the “why”. For instance, diagnostic analysis can help in understanding the reason behind a sudden drop in customers for a company.
  • Predictive This, as the name suggests, helps in predicting the future course. This is done through actionable, data-driven insights which businesses can use to plan their future.
  • Prescriptive This kind of analytics helps in understanding how predicted outcomes can be used. This is a complex type of analytics involving algorithms, machine learning, and computational modelling procedures.

For performing data analytics, data analysts require a few important tools like Python, R, Tableau, Power BI, and SAS. We’ve described them briefly below.

Data Analytics Tools

  • Python – This object-oriented open-source programming language is used for manipulating, visualizing, and modelling data.
  • R – An open-source programming language used in numerical and statistical analysis.
  • Tableau – This helps in creating several kinds of visualizations for presenting insights and trends in a better way.
  • Power BI – This is a business intelligence tool that supports multiple data sources, helps in asking questions and getting immediate insights.
  • SAS – This statistical analysis software helps in performing analytics, visualizing data, writing SQL queries, performing statistical analysis, and building ML models.

Data Analytics Applications

Now that we know and understand what data analytics and its types are, we should also understand the different ways in which it is used. The truth is that it has use cases across many business verticals. Here are some of the data analytics applications across different industries:

  • Retail Understanding customer needs and buying habits to predict trends, launch new products, and boost sales.
  • Healthcare Analysing patient data for lifesaving diagnosis and treatment. Data analytics also helps in developing new drugs.
  • Manufacturing Data analytics helps in solving complex supply chain issues, labour constraints, and breakdown of equipment.
  • Banking Pointing out probable loan defaulters and detecting frauds
  • Logistics Developing new business models and optimizing routes.

Be the Expert – Career Opportunities in Data Analytics

Now that you have a brief idea, let us take a look at courses for business analysts.

Emeritus India offers a whole lot of courses and programmes that are aimed at familiarizing aspirants with data science courses and data analytics courses. Achieving a certificate in business analytics or a certificate in data science can open many prospective opportunities for professionals in this field.

Emeritus brings to you these courses from some top-rated Indian institutes and universities. These courses help professionals as well as graduates in getting a certificate in business analytics or a certificate in data science.

Bing any of these courses, it is important to understand the difference between data science courses and data analytics courses. Both data science courses and data analytics courses can help a person in creating a lot of impact for an organization. They are two distinct career fields but equally important.

Its courses can help a person in seeking answers to some specific questions or challenges faced by businesses. Data science courses on the other hand help a person understand the kind of questions that organizations should be asking.

While a data analyst uses software such as Excel and programming languages including SQL, R, SAS, and Python, data scientists should be proficient in Hadoop, Java, Python, machine learning, and object-oriented programming apart from software development, data mining, and data analysis.

So, once you are clear on what you want to pursue as your career, choose any of these courses online and give your career the strategic boost it needs!

About the Author

Senior Content Contributor, Emeritus Blog
Varun, a seasoned content creator with over 8 years of diverse experience, excels in crafting engaging content for various geographies and categories. Leveraging this expertise, he seamlessly translates complex concepts into enriching educational content for the EdTech domain. His keen understanding of research and life experiences helps him resonate with students and create fact-based content. He finds solace and inspiration in music, nurturing his creativity for content creation.
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