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Understanding The Terminologies – Big Data, Business Intelligence, Business Analytics

According to a Gartner report, the worldwide market for business intelligence and business analytics is estimated to grow at $22.8 billion by the end of 2020. Today, data is expanding at a faster rate than ever before – it is predicted that by 2020, 1.7 megabytes of information will be generated per second for every single human being on this earth.

Big data is enabling organizations to harness greater value from such huge volume of structured and unstructured data that is being generated every day through various sources. Companies are able to reap greater benefits with faster decision making, cost reduction, and also enjoy significant competitive advantage by discovering meaningful patterns and relationships through their data.

In the recent years, enterprises are increasingly making investments in advanced software solutions using business intelligence tools and business analytics programs. These tools have enabled them to streamline their business operations, identify new business opportunities by gathering actionable, real-time insights leading to enhanced business performance.

These terminologies such as Big Data, Business Intelligence, and Business Analytics are used interchangeably, but there is a subtle difference between these – let us understand that.

Understanding Big Data

In simple terms, big data refers to large amounts of structured, unstructured and semi-structured data which can be used for the purpose of analysis. Gartner defines it as “Big data is high-volume, fast velocity and different variety of information assets that require an innovative platform to get improved insights for better decision making.

Big Data is a combination of 3Vs –Volume, Velocity, and Variety.

Volume: There is an exponential growth in the storage of various formats of data including video, music, text, images, sensor data, and social media. This big volume of data represents Big Data in an enterprise.

Velocity: Velocity refers to the speed at which data is coming from various sources. Over the past few years, the growth of data has transformed. Some data, such as social media data, comes in real-time and needs quick analysis for faster decision-making.

Variety: Data coming from different applications comes in different formats. It may not fit into one format because some data is structured whereas; a lot of data is unstructured. The diversity represents the variety factor of Big Data.

Understanding Business Intelligence

Business Intelligence may be defined as a set of processes, technologies, and architecture that has the ability to transform raw data into meaningful information to drive profitable business decisions. The tools used in BI access and analyze data sets for presenting analytical findings through reports, graphs, charts, summaries. These dashboards provide users with detailed intelligence about different aspects of their business.

Some of the key benefits of using BI tools include

  • Better business decisions based on solid data instead of “relying on gut-feeling”
  • Improved data quality and a single window of truth for business decisions
  • More accurate and real-time reporting and analysis
  • Better planning based on concrete information
  • Faster reporting
  • Enhanced operational efficiency resulting in reduced costs
  • Better customer acquisition and improved customer satisfaction
  • Ability to create a competitive advantage.

Understanding Business Analytics

Business Analytics may be defined as “a set of skills, technologies and practices for continuous repetitive exploration and assessing past business performance for deriving insight and improving business planning.

It mainly focuses on using statistical methods and predictive modeling to develop new business insights and predicting future trends. Companies using business analytics solutions are able to make effective data-driven decisions to automate and optimize their processes.

Some of the key benefits of using business analytics include:

  • Better decision making and better alignment with business goals and objectives
  • Ability to transform data into actionable insights
  • Ability to identify key trends and patterns from data and take timely business decisions based on those
  • Gain clearer insights into customer behavior and use that information to enhance the overall customer experience
  • Gain a single unified view of the entire enterprise information

Difference Between Business Intelligence (BI) and Business Analytics (BA)

While inter-related, let’s understand how these two terms are different –

  • BI focuses on the present while BA is for the future. BI focuses on improving the operational efficiency by analyzing historical and real-time data to enable the stakeholders to perform effectively. Business Analytics, on the other hand, explores the data through statistical analysis, quantitative analysis, and predictive modeling to identify trends. By acting on these trends, organizations can change the course of their business.
  • Business Intelligence, focuses on repetitive reporting templates that help in extracting specific information. Post analysis, this information is then presented in a pre-defined format. BA starts with a question and then uses statistical and quantitative data and deep research to provide insights on the question.

Conclusion

Irrespective of the size and type of business, Business Intelligence and Big Data Analytics solutions assist enterprises in making faster decisions with the focus on continuous innovation and sustained profitability.

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