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What Is The Difference Between Business Intelligence And Data Analytics?

This entry is part 2 of 3 in the series Data Analytics Questions People Also Ask Google

When it comes to Business Intelligence (BI) or Data Analysis, both these terms are used interchangeably these days. However, they don’t mean the same thing although they are both used to make better data-driven decisions.

The primary difference between Business Intelligence and Data Analytics is that BI helps in making decisions based on past results while data analytics aids in making forecasts for better operational efficiency.

What Is Business Intelligence (BI)?

Business Intelligence (BI) is an aggregation of all the processes and procedures that are involved in data collection, sharing and reporting so that better data-driven decisions can be made.

Traditionally, BI deals with analytics and reporting tools, that help in determining patterns using available data. Insights from Business Intelligence help businesses achieve efficiency using real-time data.

The actionable information derived using BI tools influence the shaping of new strategies and revision of old ones. This is the reason why BI has become indispensable to organizations that handle huge volumes of data.

What Are The Types of BI tools?

Major BI tools include

  • data analysis applications
  • data visualization software

The other commonly used technologies include

  • Data Warehousing
  • Dashboards
  • Ad Hoc Reporting
  • Data Discovery
  • Cloud Data Services.

What Are The Benefits Of Business Intelligence?

Below are the most important benefits of Business Intelligence:

  • Helps track performance as well as progress when it comes to the achievement of business goals.
  • Employs quantitative analysis through predictive and statistical analytical models.
  • Facilitates better collaboration between internal and external businesses and clearer reportage of raw data.

What Are Data Analytics?

Data analytics stands for all the qualitative and quantitative processes through which data can be extracted, categorized and analyzed to create make better business decisions. It uses statistical and/or logical techniques to describe, illustrate and evaluate data.

What Are The Different Types Of Data Analytics?

Based on the phase of workflow and the kind of analysis required, there are 4 major types of data analytics. These include the following:

  1. Descriptive analytics
  2. Diagnostic analytics
  3. Predictive analytics
  4. Prescriptive analytics

Read more about the different types of data analytics here.

What Are The Benefits Of Data Analytics?

Businesses with foresight that use data analytics have the following benefits:

  • Design better business initiatives through an in-depth understanding of the needs of the customer and organization!
  • Develop a competitive edge over competitors from the insights derived from data.
  • Improve customer satisfaction by paving way for personalization.
  • Optimize business operations and operational efficiency.
  • Prevent fraud, data breach, and other threats.

At the very core, BI and data analytics are more alike than different. Sophisticated BI tools and Data Analytics will drive the making of effective business decisions and the execution of appropriate actions. Both of these have been proven to be useful for business enterprises in today’s digital age that’s exploding with data.

Are you still wondering how to become a data analyst, then this blog post is for you!  If you are intrigued to know more about data analytics and its nuances or maybe even make a career out of it, please check here more details.

Series Navigation<< What Are The Different Types Of Data Analytics?What Are The Skills Required For A Data Analyst? >>

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