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How Does Data Mining Help A Business Intelligence Platform?

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    Since the beginning of the 21st century, the corporate economy has been driven by its lifeblood data. Even though the thought of it may bring up strange images, the truth is that data is the key to making people more productive in all areas of life. 


    Data mining for a Business Intelligence platform is just as important as finding the right product-market fit for a business that is ready for the future and can run on its own. It helps plan the company's future, develop new products, and do many other things that help keep the bottom line healthy. 


    This blog discusses what is Business Intelligence and data mining and how data mining is used to ensure steady revenue streams. 

    How vital is data mining for businesses? 


    Data mining aims to look through vast amounts of data to find connections and patterns that haven't been seen before. These can be used to solve problems in a business. Companies can use tools and data mining methods to predict market changes better and act confidently on that information. 


    Data mining is one of the most critical parts of data science. It uses cutting-edge analytical techniques to find useful information in large data sets. Data mining is one of the steps in the knowledge discovery in databases (KDD) process because it is a data science method for collecting, cleaning, and analyzing data. Even though data mining and KDD are sometimes used interchangeably, they are usually seen as two different fields of study.

    What value does data mining add to a BI tool?

    Most of the time, experts in business dashboard software and analytics are the ones who mine data. But this can also be done by business analysts, executives, and other employees who are not paid. 


    Its main parts are Machine Learning, statistical analysis, and data management to prepare it. Machine Learning techniques and Artificial Intelligence (AI) tools have made it easier and faster to mine large amounts of data, such as customer databases, transaction records, and log files from web servers, mobile apps, and sensors. 


    There are four different stages of data mining: 

    Information Gathering

    Information that can help with running an analytics program is gathered. The data may be in different source systems, a data warehouse, or a data lake, which is becoming more common as a place to store big data. You can also access information from external sources. No matter where the data comes from, data scientists usually keep their results in a "data lake" before moving on. 


    A Business Intelligence platform like Grow collects data from multiple sources and provides actionable insights. To know more, read Grow Features & Capabilities GetApp

    Getting the data ready 

    In this phase, we do what we need to get the data ready for mining. First, the data are explored, profiled, and pre-processed. Next, the data are cleaned up to fix mistakes and other quality issues. But unless a data scientist is specifically asked to look at raw data in its unprocessed form, all collected data sets are changed in some way to ensure they are all the same. 

    Data Mining

    In applications that use machine learning, algorithms are often trained on a smaller subset of data to find the information they need before they are used on the whole dataset. After gathering and cleaning the data, a data scientist will choose the best data mining method and put the needed algorithm into action (s). 

    However, many tools offer Business Intelligence dashboards that do not need any technical expertise on your part

    Using and Analyzing Data 

    Data mining results are used to make analytical models that guide how a business works. Another important job of the data scientist or another data science team member is to share the results with company leaders and users.


    Grow’s BI tools offer at-a-glance dashboard reports to everybody on your team. To truly learn what is Business Intelligence, one needs to ensure the integration of data mining techniques. 


    Closing Words-


    Using Grow's Business Intelligence dashboards, marketers can use the insights gained from data mining to better tailor their promotional efforts to the tastes of their target demographic. Our data mining efforts can also help your sales teams to

    1. Increase the percentage of leads who become customers
    2. More attentive customer service
    3. Manage the supply chain better
    4. Availability of management process
    5. Save on costs
    6. Increased security measures

    Are you ready for transformation?


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