Business

What is Business Intelligence?

Business Intelligence

Facts about Business Intelligence Market:

  • If Gartner is to be believed, the global Business Intelligence and analytics market reached USD 24.8 billion with a compound annual growth rate (CAGR) of 10.4% in 2019.
  • It reached USD 27.4 billion in 2020 and is expected to reach USD 29.48 billion by 2022.
  • Around 72% of organizations believe that business intelligence is crucial to their daily operations.
  • The banking sector makes up the largest BI consumer market, with 13.9% of the BI market’s total revenue. 
  • It is expected that through our activities, we will produce 44 zettabytes of data every day.
  • The industries that most frequently consider Business Intelligence crucial to their operations are retail, wholesale, and finance.

Good News:

The demand for qualified business analysts and managers is anticipated to increase by 14% by 2026, according to the US Bureau of Labor Statistics. Also, data professionals’ overall need is expected to increase by 28% in 2020 and after that. 

To make a career in the domain which is ever-evolving and innovative, with scope across the world, taking up a data analytics course from a reputed institution can be rewarding. Let us explore what Business Intelligence is and how a career in this domain can be beneficial.

What is Business Intelligence?

Business Intelligence is an umbrella term that covers technologies, applications, and practices for the collection, integration, analysis, and interpretation of business information. BI utilizes software and services so that the data can be transformed into actionable insights. The insights gained informs about strategic and tactical decisions of the business. 

The term Business Intelligence also covers the range of tools and techniques that allows quick and easy-to-digest access to valuable insights regarding the current state of an organization based on available data. There are BI tools that enable you to access and analyze data sets and current results of analytical reports, dashboards, summaries, charts, graphs, and maps that provide users and stakeholders with the current position of the business. 

Essentially, Business Intelligence systems are considered data-driven Decision Support Systems or DSS. to make the decisions data-driven, BI combines data mining, business analytics, data visualization tools and techniques, and best practices.

The process of Business Intelligence include:

  • Data Mining: utilize database, machine learning, and statistics to identify trends in huge datasets.
  • Reporting: to prepare data analysis reports to be shared with stakeholders to draw conclusions and take decisions. 
  • Performance Metrics and Benchmark creation: to compare current data related to performance to historical data enabling you to track performance against goals, generally utilizing customized dashboards.
  • Descriptive Analytics: to perform primary data analytics in order to identify what happened.
  • Querying: to ask the questions that are data-specific and BI extracts the data from the datasets. 
  • Statistical Analysis: the results from the descriptive analysis are taken to explore them further using statistical methods. 
  • Data Visualization: this step involves the transformation of data analysis into visual representation such as graphs, charts, or tables.
  • Visual Analysis: to explore the data via visual presentation in order to interpret insights on the fly and stay in the analytical flow.
  • Preparation of Data: to compile various data sources, finding out dimensions and measurements so that data can be prepared for analysis. 

Let us now see how Business Intelligence makes a difference if implemented in an organization. Some of the ways in which BI enables companies to make better data-driven decisions are:

  • Accurate reporting, analysis, or planning
  • Performs analysis of customer behavior
  • Compares the current and historical data of competitors
  • Tracks the company’s performance
  • Improved data quality
  • Improvement in operational efficiency
  • Predicts success rate
  • Identifies problems or issues

Business Intelligence Vs. Data Analytics

We have read a lot about Business Intelligence. Now let us read what data analytics is and then compare both the technologies.

Data is something that tells us about the past as well as the future. Data Analytics refers to the process of analyzing raw data to identify trends to answer the questions. It is a process that involves inspecting, cleaning, transforming, and modeling the data so that meaningful conclusions can be drawn to support better decision-making.

While analysis refers to the process of looking back at historical data to identify what happened in the past, analytics is the process of identifying such patterns that help in predicting future events.

  • So, while Business Intelligence is all about looking at past events, data analytics focuses on future events. 
  • When ordinary users can perform Business Intelligence, you need experts for performing data analytics.
  • Business Intelligence answers the questions that ask What, while data analytics is capable of answering the questions that ask Why.
  • It is only data analytics that is capable of interpreting unstructured data
  • If you need more predictable outcomes, you should go with Business Intelligence as BI is the one that generates more predictable outcomes than data analytics.
  • To collect, cleanse, verify, and integrate the data, both of the disciplines require skilled and trained professionals. Generally, this process involves an automated ETL process and a data repository such as a warehouse.

One thing to be kept in mind is that BI and Data analytics work together, both having different use cases. BI is rendered ideal for day-to-day operations, and data analytics helps an organization in shaping up strategies. So, instead of considering both the techniques as separate technologies, it is time to realize that both of the activities should be executed in parallel. 

The most common thing in Business Intelligence and Data Analytics is that both of them require a continuous supply of fresh and reliable data. There are many ETL tools that serve both the purposes of analysis and analytics. Expertise in such tools may let you make your career skyrocket.

Conclusion

By now, you might have realized that BI and Data Analytics both are crucial for an organization as they should be executed side-by-side. If you acquire expertise in tools that serve both purposes, you may become the most preferred candidate for the recruiters. 

Taking up an online training course is one of the most sensible steps that can enable you to attain mastery of such tools. Apart from choosing learning hours and mode of learning, you get job assistance as well. 

Get yourself enrolled now!

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