Sisense
OCTOBER 21, 2020
As a member of the data team, your role is complex and multifaceted, but one important way you support your colleagues across the company is by building and maintaining data models. Picking a direction for your data model. Think like a designer. However, just asking your users, “What do you want?”
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.
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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.
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
JUNE 15, 2021
With a robust data model built using data from their disparate datasets, they had a full-spectrum view into how their marketing efforts were performing in different parts of the world, as well as which games were more popular where. Ashley is passionate about data, analytics, AI, and machine learning.
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.
Sisense
MAY 21, 2020
Net new use cases allow new and better access to tools that help democratize insights to enable better decision making,” says Naveen Punjabi, lead for data analytics partnerships at Google Cloud. “We Data Freedom is a key focus and by better understanding customer needs, we will create more packaged solutions.”.
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