data-requirements 
Domo
JULY 8, 2021
Since the introduction of the cloud, a steady stream of companies has opted to move its most sensitive data from on-premises to remote storage, making it available from anywhere and in real time. A third thing you should consider is how providers align with your data governance models.
Domo
MARCH 12, 2021
As companies dig more deeply into their digital transformations, they’re finding more data that has value. But there’s another card in the data deck to play: commercializing data for revenue. For example, LexisNexis has spun out its legal-spend data into a SaaS offering to help companies better manage these expenses.
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Data Pine
FEBRUARY 17, 2023
3) The Link Between White Label BI & Embedded Analytics 4) An Embedded BI Workflow Example 5) White Labeled Embedded BI Examples In the modern world of business, data holds the key to success. That said, data and analytics are only valuable if you know how to use them to your advantage.
Sisense
FEBRUARY 10, 2021
In order to do this, my team uses data to identify problem areas and potential issues for our customers (ideally before they happen). Like many organizations, our utility company clients are sitting on copious amounts of data from a variety of sources, including mobile applications and streaming data captured by grid-edge technologies.
Data Pine
NOVEMBER 27, 2019
Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. Suddenly advanced analytics wasn’t just for the analysts.
Insight Software
NOVEMBER 14, 2023
In today’s data-driven world, having accurate, timely insights into data is critical. When your operational and financial reporting teams are extracting and transforming Oracle E-Business Suite (EBS) data, it can be a complex, cumbersome task and they need a way to handle data that empowers them to overcome reporting obstacles.
Insight Software
FEBRUARY 23, 2024
The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.
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