Business Intelligence Guide 2021: All You Need to Know


If you have problem-solving skills, specific industry knowledge, communication skills, advanced vision and attention to detail, data analysis, business shrewdness, then you are going to succeed in a Business Intelligence (BI) career. 

Exactly, Business Intelligence means being quick-witted about your business, so that it can help companies make better choices by showing existent and authentic data within their business environment. 

It can solve issues in poor production management, slow market reaction, losing clients, commotion in day-to-day performance, wasting time on organizing different systems rather than Analyzing data, dependence on tech teams to progress custom reports, restricted access to data. 

Common basic tasks of Business Intelligence include:

  • Reporting
  • Online analytical Processing
  • Analysis 
  • Development of the Dashboard
  • Mining of the Data
  • Process Mining
  • Complex Event Operations 
  • Business production management
  • Benchmarking
  • Text mining
  • Predictive Analysis
  • Perspective analytics

They discovered in a recent survey that about 98.6 percent of Fortune 1000 companies are adapting to data-driven lifestyles. Already about 32.4 percent have converted fully into a data-driven lifestyle. 

They found that data-driven culture has made the business competent, cost-effective, and is often fast to disruptive opportunities. 

Why Business Intelligence?

Earlier, they used to print often lengthy sheets of metrics and key performance indicators (KPIs) like sales and toss the numbers. They found these printouts useful to managers and executives, but they lacked the complete picture of the company’s production. 

As they created more statistics, outside the company’s database, it made the organization lookout for a desperate alternative to collect and visualize the data. That’s how Business Intelligence came into the picture.

Some ways on how that Business Intelligence can assist organizations to make perceptive, data-driven resolutions are:

  • Connect ways to increase profit
  • Explore customer behavior
  • Differentiate data with competitors
  • Trace performance
  • Adjust performance
  • Expect success
  • Notice market trends
  • Locate issues or problems
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How to execute BI?

Every Business Intelligence is distinctive in its need, and the steps required to execute it depend on its relevant requirements. Some skills and steps required to execute are:

  1. Probability study:

Surveying the existing business requirements and data circumstances so that they can implement which software will be sufficient is the first step. It will require about 4-6 weeks for this procedure.

  1. Engineering demand:

This step involves defining effective and non-effective requirements for a BI solution. It can be mandatory or optional.

  1. Approach and plan of action:

Plotting the preferred solution to the requirements, defining the craving BI solution analysis, requires an automation stack and skills to complete the project. Also, fixing data sources and ETL strategies, along with data quality affirmation tasks, BI operation, and user approval plan. As a solution, the project team designs the solution architecture with a detailed list. 

  1. Project Planning:

Some steps taken to fulfill the project plans are defining output, evaluating risks, evaluating BI implementation costs, TCO and ROI. 

  1. Development:

Providing the back end and front end of the BI solution, executing ETL processes for each of the data origins, framing up data quality management and data quality are some methods followed. They ensure it runs quality assurance procedures to avoid problems such as wrongly evaluated KPIs, slow BI reaction, or low-quality UX. It has to be noted that these procedures take upto 3-4 months. 

  1. User-training:

Providing end-users with user manuals and coaching sessions, altering common systems for each user group, etc.

  1. Launch:

In real-world scenarios, it is necessary to check the pre-launch user acceptance in the BI solution. So that they can deploy with the solution in production, and it will be ready for end-users to employ. 

  1. Solution support and expansion:

The team can upgrade the solution with self-service competence, up-to-date business analytics, and data science ability, etc.

Business Intelligence Mode in 2021:

They predict that these are the mode that will hold in 2021:


The no-code movement allows people without technical or data analytical capability to replace the no developer. Anybody can sense and alter the data and visualize, clarity, or part, without a single line of code. No-code allows everyone to be data-driven. Some of the well-known tools are Airtable, Zapier, and Typeform. 

Self-serve Analytics:

Reporting on business intuition is no longer solely reserved for data analysts. Modern BI tools are adjustable and allow self-serve analysis. One can easily login to the BI software and collect the edible and practical data you need. This is done instead of creating reports from data that are viable in spreadsheets and also in presentation decks. Data Analysts or IT titles are no longer needed to access and design reports.

Lightweight BI:

Lightweight BI avoids the costs and complications when traditional BI solutions are complex, inaccessible, and need the technical ability to access data. 

You don’t need to have any technical chops as Lightweight BI is mostly low or no-code.    

You can explore the data to the fullest with just a click to visualize data into charts, or filter and segment.

It just takes 10 minutes or fewer to build a dashboard with just login credentials in a Lightweight BI tool.  

Data Democracy:

You can make smarter business decisions when you get insights from data. Everyone can use data strategic decision-making when data democracy removes barriers. 

Data democracy functions with the following principles:

  1. The average user can access details in any digital format. 
  2. No need for any help to gather and analyze data for the non-specialists. 
  3. Have to protect individual private data.
  4. Should have data quality. 
  5. For authorizing non-technical people in data democracy, pillars in technology like Augmented Analytics, NoSQL, dashboards, and self-service tools are used. 
  6. Need guidance by data ethics.

Employees from the whole organization are aware, can access, take part in using the data for their day-to-day work and also in decision making. 

Future of Business Intelligence:

All the companies need to develop Business Intelligence software as it streamlines the workflows to enable ease of use and predict abilities. 

For it to develop, we need these strategies:


The tools make us collaborative and facilitate teamwork at ease


Third-party systems will be increasingly interlaced with BI.

Machine Learning:

To provide insights and forecasting, Artificial Intelligence (AI) analyzes past data.

Data Proactivity:

This feature brings relevant data to users and responds automatically to inquiries. 

Network Advancements:

This supports business intelligence systems as technology infrastructure will expand to store a huge amount of data.

Data driven culture:

This involves giving all employees the resource to incorporate BI in everyday processes. 

To conclude, this describes some of the modern technology in BI, to enter the era of Big Data. The future is going to be more technology-based and aggressive to use. In simple words, the future of business is in Business Intelligence. 

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