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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Both data warehouses and data lakes are used when storing big data. Many people are confused about these two, but the only similarity between them is the high-level principle of data storing.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.

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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable.

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games. This analytics engine will process both structured and unstructured data. “We