Data Lake Data Strategy Digital Transformation Strategy 
BI-Survey
NOVEMBER 23, 2021
Thus, alternative data architecture concepts have emerged, such as the data lake and the data lakehouse. Which data architecture is right for the data-driven enterprise remains a subject of ongoing debate. Data black holes: the high cost of supposed flexibility. Data Black Holes.
Alation
OCTOBER 21, 2021
Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.
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BI-Survey
DECEMBER 22, 2020
Managers see data as relevant in the context of digitalization, but often think of data-related problems as minor details that have little strategic importance. Thus, it is taken for granted that companies should have a data strategy. But what is the scope of an effective strategy and who is affected by it?
Sisense
DECEMBER 23, 2019
AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Once your data is prepared for analysis, the next question is: how else can AI help you? It’s also a better way to monetize your data in the short term. It’s the future.
Cloudera
JULY 26, 2021
With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.
Cloudera
JANUARY 30, 2024
While AI stands to drive smart intelligent factories, optimize production processes, enable predictive maintenance and pattern analysis, personalization, sentiment analysis, knowledge management, as well as detect abnormalities, and many other use cases, without a robust data management strategy, the road to effective AI is an uphill battle.
CIO Business Intelligence
FEBRUARY 16, 2023
Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.
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