Stacking Data For BI Reporting Tools To Work

 Business leaders need help to get a clear picture of what's going on in their organization and how to steer it in the right direction when things are set up this way. Business Intelligence reporting tools can help when you plan them well. 


How can they make sense of it and use the data to add value if it isn't organized? 


The answer is simple: make a data stack that acts as your Business Intelligence architecture. This architecture is a framework that combines all the different technologies used to visualize and analyze data. It's a full flow of the IT systems and software tools responsible for one or more parts of the overall stack, like collecting, storing, or analyzing BI data. Business users can get something useful from data when the stack is in place.


Stacking Up BI data for Business Intelligence Reporting Tools To Work Well


Different Components That MakeUp A BI Data Stack:


1) the technical parts of the stack itself, and

2) the functional parts related to methodology and organization.


Technical parts support the BI process to create the best Business Intelligence tools.


  1. Source systems: Collect data from databases, CRM and ERP systems, files, APIs, the marketing stack, and other scattered data sources. Here, data has already been entered and exists. This is a good place to start because data needs to be gathered and put in one place before it can be changed and turned into something useful.


  1. Data integration: The collected data is integrated into a centralized system, most commonly through an ETL process (Extract, Transform, Load). There is plenty of ETL software available, but the best Business Intelligence tools with ready integration come with pre-existing data connectors with a wide variety of sources to make this a seamless process.


  1. Data storage: Data warehouses must scale as usage goes up and become fundamental to the success of your BI projects. They are now cheaper and easier to get than ever before. Data storage is becoming more sensitive, so make sure you know where your data and the data of your customers live.


  1. Transformation: Transformation happens where the raw data in the data warehouse gets transformed into actionable business data. Solutions like dbt, Whaly and y42 help with this stage.


  1. Analysis of the data: With the help of the right tools, the data is visualized, usually in the form of graphs, dashboards, and charts, and analyzed so that business teams can start to make sense of it. Business Intelligence software companies can help you take it to the next level in terms of user-friendliness and ease of use. 


  1. Ad-hoc data discovery: After that, data analysts can start answering new business questions in a ‘sandbox’ where they can try out new ideas. 


  1. Data cataloging: It means keeping an organized list of all the data assets in an organization so that data analysts can find the data they need quickly. 


  1. Data distribution: Once the data has been visualized, it can be sent out in different formats, such as dashboards, to help businesses make strategic decisions. With the Business Intelligence reporting suite, you can push it in the format that you or your stakeholders want so that it can be used in the best way.


Functional parts that will help you do well:


  1. Set up your team: A single person or team will be in charge of data topics, defining data metrics, and handling requests in a centralized way.


  1. Define key success metrics with business users: By setting success metrics ahead of time, you can get your business teams on the same page for expected goals and expectations. 


  1. Iterate with the business teams: The business teams should take part in a workshop to define metrics or even lead it. In the end, the end users are the ones who know the most about what the business needs. The data team should give them information to help them figure out what is possible with the solution as it is now. The more you work with the business teams throughout the process; the more likely the project will go well. 


  1. Measure how the data project affects your business: If you don't measure, how will you know if it's successful or worth it? Keep track of how many insights have been made and how much money the project has made.


The goal is to find actionable insights from the data and have the business use them to make data-driven, well-informed decisions about the company's finances, revenue, and growth. Stacking up a Business Intelligence reporting suite the right way definitely helps. 


Closing Words-


If you want to learn more about integrated and self-service Business Intelligence reporting tools or go deeper into the stack. Read more about Grow Pricing 2022 Capterra to understand better. 

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