Data Analytics Data Modelling Embedded Analytics Innovation 
Sisense
MARCH 14, 2021
However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.
Sisense
JULY 8, 2020
Many cloud data warehouses offer compute scaling that allows for dynamic scaling when needs spike. This allows data teams to still see scalable performance while holding increased numbers of computationally expensive data models and ingesting more large data sources. From ETL to ELT and beyond.
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Sisense
MAY 11, 2021
You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Building the right data model is an important part of your data strategy.
Sisense
MAY 21, 2020
It highlights an important fact, that companies are looking towards data to deal with extreme changes , and sophisticated BI tools can guide that approach to analyze sophisticated data and deliver basic insights back to organizations. Focus on integration and innovation. Moving data into the cloud, driving innovation.
Insight Software
MAY 1, 2023
Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.
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