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    Home»Business»Capturing value from big data and advanced analytics
    Capturing value
    Capturing value
    Business

    Capturing value from big data and advanced analytics

    CamillaBy CamillaSeptember 28, 2022Updated:October 8, 2022No Comments3 Mins Read
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    Table of Contents

    • Capturing Value From Big Data and Advanced Analytics
      • 3Vs of big data challenge the fundamentals of existing technical approaches
      • Importance of senior-executive sponsorship for big-data initiatives
      • Importance of hiring people with analytical horsepower
      • Importance of understanding the meaning of big data

    Capturing Value From Big Data and Advanced Analytics

    While big data is a growing area of business, there are some critical challenges that traditional organizations still face. Here are three ways to make sure your big-data strategy is successful: appoint analytical horsepower; secure senior executive sponsorship; and understand the nuances of big data.

    3Vs of big data challenge the fundamentals of existing technical approaches

    Defining big data can be complicated, but one framework describes the three key factors that define the field: volume, velocity, and variety. Big data is becoming a more complex problem to solve, and there are several ways to handle it. The 3Vs of big data describe three main challenges for enterprises and their analytics teams.

    The first challenge is figuring out which data to use. This data is heterogeneous and can come in both structured and unstructured formats. While it is relatively easy to store and analyze structured data, the unstructured data presents new challenges. Therefore, big data solutions must be able to handle a variety of data types. The 3Vs of big data challenge the fundamental approaches to data storage, analysis, and visualization.

    Importance of senior-executive sponsorship for big-data initiatives

    Executive sponsorship is a key component of successful data initiatives. It provides motivation and executive coaching skills, as well as significant resources. In turn, executive sponsorship benefits the entire organization. Without it, big-data initiatives can fall flat. To get the right executive sponsorship for your big-data initiative, make sure you have the right leadership in place.

    It is essential that the sponsor be able to understand the full impact of the initiative. It is important to understand how this technology will impact the culture of the company, and he or she should be able to oversee the implementation process without becoming micromanaging. In addition, the sponsor should be willing to accept the challenges that come with the initiative, and it is critical that he or she understand the full scope of the initiative.

    Importance of hiring people with analytical horsepower

    Companies are increasingly turning to big data and advanced analytics for strategic business decisions. As the volume and diversity of data grow exponentially, the need to employ sophisticated analytics techniques grows. Organizations need to actively manage and process this data in order to realize maximum value. Today’s organizations face challenges in gathering and managing this data. The ability to extract valuable knowledge from data is a valued asset in today’s business.

    While big data is an important strategic tool for businesses, it also carries its own risks. Without the expertise of an analytics team, companies may fail to make the most of their data. As a result, they may experience a loss of business. Additionally, big data can result in security breaches or even hacking.

    Importance of understanding the meaning of big data

    Big data is a collection of massive amounts of data that is difficult to process using traditional methods. It comes from millions of sources around the world and is generated at an incredibly rapid rate. Some of these sources are social media platforms, which generate hundreds of terabytes of data each day, including pictures, videos, messages, and other information.

    Big data is often classified into three types: volume, variety, and velocity. These three dimensions describe how big data is collected, processed, and stored. Using big data for a business’s decision-making purposes requires speed, high-speed data capture, and sophisticated analytics.

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