Data Analytics and Business Intelligence, namely BI solutions, are important for managing modern business. Interestingly, the terms are often used interchangeably. But do they have the same meaning? And yes, what is it?
Data Analytics and Business Intelligence have different scopes of work so they require a varied set of skills for helping companies achieve success in efficient data-driven operations. While Data Analysts proceed with in-depth analysis, Business Intelligence makes sure the requirements of data reports are correct.
Let’s see the concepts hiding behind both terms. This will help you make the right choice between Data Analytics and Business Intelligence for your own company.
Descriptive, predictive, and prescriptive analytics
BI solutions are known as a set of methodologies, architectures, and technologies that process raw data into meaningful information, which enables more effective decision-making.
Data analytics is the process of collecting, examining, transforming, storing, and organizing data along with other related operations. Now that you know the general definitions of both terms, you may need to understand the differences between them.
BI is considered to be backward-looking as it delivers descriptive analytics. It allows companies to answer questions about past processes. How many things did you sell? Which kinds of goods were sold? When did we have the most customers?
Data analytics is focused on future events. It often delivers predictive analytics that predicts potential outcomes. For example, it includes the sales forecasts and the analysis of engines delivering business suggestions on e-commerce websites. Depending on the applied algorithms used, the forecasts happen to be more valuable to companies than the descriptive analytics obtained from BI.
Don’t forget about the highest level of data analytics – prescriptive analytics that provides a piece of advice to companies. It aims to predict the outcomes and suggest the actions that might lead to the most desirable outcomes.
Data in, analytics out
The more data you collect, the more useful it can be for your business company. Benefiting from your data requires multi-level data analytics software. You may consider using one of the most popular tools like Google Data Studio and Metabase, which can generate incredibly accurate reports.
More advanced BI tools like Tableau and Looker have already proved their efficiency in the business sector. They offer effective customization and functionality at a high level. Well, data scientists have enough resources to develop custom data analytics applications by reaching an even higher level of productivity.
Are you a beginner in data analytics and BI tools? Then, you will put a data analytics stack together by means of the analytics software. Just make sure to find the software that will help you manage all the analytics you want.
Which BI tool is the best? This question may have hundreds of answers. The reality is that it depends on what you are trying to achieve in your business activities. Importantly, you don’t start your business analytics from scratch and already have technology systems integrated.
You should know that some further investment in analytics can help you integrate decision management tools into your existing business environment. However, the main thing is to understand how you will eventually manage your analytics within your daily operations.
Different applications are intended for different purposes. To keep single simple, you may consider using Excel for analytical purposes. No matter how simple and even ridiculous it may sound, you shouldn’t ignore it. Well, you may consider using more complex programs like Python.
All of the reporting tools can use the data stored in a central analytics repository, also known as a data warehouse or data lake. A data warehouse requires a schema for storing tables, records, and columns, while a data lake doesn’t store anything so a schema isn’t required. In this context, the analytics software can be used to infer records and columns, we well as to process valuable data and store it for reporting purposes.
To fill in a data warehouse, you need to collect a certain amount of information. This can be achieved with a data integration tool that will replicate new data and transfer it into a repository. There are more than enough resources to extract data from. The best thing is that it can be done on whatever schedule looks good to you. Ideally, it addresses the needs of the company that generates BI.
The goal: better business outcomes
Whether you’re a business manager trying to optimize productivity or a supervisor aiming to enhance the company’s performance, you will definitely benefit from data analytics and business intelligence.
Empower your company with the ability to assess the whole range of potential opportunities. This requires a variety of insights, advanced analytics, and decision-making to explore the various scenarios in real-time. To do this, you need user-friendly decision management tools like BI solutions software.