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Data Terms Glossary

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BI Reporting Tool

Unlike money, it’s really easy to acquire data. Most companies are positively drowning in it. The secret to turning all that data into money is to unlock its value—to manipulate, analyze, and summarize the data into knowledge that can be used to monitor the health of the business and make decisions, whether day-to-day operational decisions or long-term strategic decisions.

The two related secrets to unlocking the value in data are:

– Having good business intelligence (BI) tools
– Knowing how to use them effectively

A BI tool provides business intelligence by analyzing data, creating it in the first place, fetching it, or changing it in some way.

There are many kinds of BI tools, from rudimentary to sophisticated.

Business intelligence applications include:

-Data warehouses: These systems centralize and organize summarized data from multiple data sources.

-Digital dashboards: These tools enable real-time monitoring of business activity in a simple graphical format.

-Online analytical processing (OLAP): OLAP tools enable users to view data from different perspectives. Users can “slice and dice” data into pre-defined or ad hoc reports and “drill down” to look at the details. OLAP tools typically operate hand-in-hand with data warehouses.

-Reporting and querying software: These applications are specifically designed to extract, sort, summarize, and present selected data.

-Spreadsheets: Modern spreadsheet applications include tools to summarize data and represent it graphically, such as pivot tables and many types of charts and graphs.

…and many others.

Traditional BI reporting tools required some level of technical expertise in the tool as well as detailed knowledge of database theory and data science. In some cases, coding skills in languages such as Structured Query Language (SQL) and general-purpose programming languages are required. Modern tools, such as Microsoft Power BI, eliminate much of the needed technical expertise by providing point-and-click interfaces, which enables “self-service BI.”

The trouble is, some knowledge of database theory and how to effectively combine data from different sources is still needed in order to produce meaningful reports and dashboards. Businesses that want to leverage these tools need to have a process for validating the output before relying on it for critical business decisions.

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