Domo
JULY 8, 2021
It’s also important to think about how you’re going to manage your cloud vendors/providers. In order to manage your infrastructure such as networks, storage, services, data management, and virtualization, you’ll likely be working with several cloud providers, including cloud data integration and cloud BI providers.
Timo Elliott
JANUARY 22, 2019
They bring insights to users rather than forcing users to unearth elusive trends, and provide more intuitive interfaces that make it easier to get the data people need to do their jobs. Embedded analytics accelerates. The historical line between operational applications and analytics continues to blur.
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Data Pine
NOVEMBER 27, 2019
Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.
Insight Software
MARCH 4, 2024
Navigating the Data Maze: Challenges in the SAP Landscape For SAP users, data management can feel like a labyrinth, fraught with obstacles and frustrating dead ends. The burden of manual data entry looms large, with endless spreadsheets consuming valuable time and resources. Want an extra layer of assurance?
Insight Software
SEPTEMBER 26, 2023
Data Cleansing Imperative: The same report revealed that organizations recognized the importance of data quality, with 71% expressing concerns about data quality issues. This underscores the need for robust data cleansing solutions.
Insight Software
OCTOBER 4, 2023
Addressing these challenges often requires investing in data integration solutions or third-party data integration tools. Excel-based SAP tools can automate data entry, report generation, and other routine activities, allowing financial professionals to focus on more strategic and rewarding aspects of their roles.
Insight Software
JULY 17, 2023
One of the major challenges in most business intelligence (BI) projects is data quality (or lack thereof). In fact, most project teams spend 60 to 80 percent of total project time cleaning their data—and this goes for both BI and predictive analytics.
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