Big Data Data Processing Reporting Unstructured Data 
FineReport
APRIL 26, 2023
This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. With the right Big Data Tools and techniques, organizations can leverage Big Data to gain valuable insights that can inform business decisions and drive growth.
IBM Big Data Hub
OCTOBER 3, 2023
Each football season, millions of articles, blog posts, podcasts and videos are produced by the media, offering expert analysis on everything from player performance to injury reports. However, the challenge lies in harnessing the wealth of “unstructured” data that permeates the sports media landscape.
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AWS Big Data
MARCH 10, 2023
Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.
datapine
JUNE 5, 2019
Without the existence of dashboards and dashboard reporting practices, businesses would need to sift through colossal stacks of unstructured data, which is both inefficient and time-consuming. Because a huge amount of data existed in a company’s mainframe computer (particularly data related to profits, costs, revenue, etc.),
IBM Big Data Hub
FEBRUARY 2, 2023
In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.
Sisense
OCTOBER 6, 2020
All descriptive statistics can be calculated using quantitative data. It’s analyzed through numerical comparisons and statistical inferences and is reported through statistical analyses. Despite its many uses, quantitative data presents two main challenges for a data-driven organization.
AWS Big Data
MARCH 2, 2023
Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.
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