Big Data Blog Data Science Structured Data 
IBM Big Data Hub
SEPTEMBER 19, 2023
Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.
Rocket-Powered Data Science
JULY 19, 2023
The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.
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Smart Data Collective
SEPTEMBER 23, 2020
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. However, a data lake functions for one specific company, the data warehouse, on the other hand, is fitted for another.
Cloudera
JUNE 7, 2022
We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.
IBM Big Data Hub
AUGUST 28, 2023
One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.
AWS Big Data
JUNE 6, 2023
This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. The Data Science teams also use this data for churn prediction and CLTV modeling. Given that the only source to access all raw data is by exporting it to BigQuery (first), data accessibility becomes challenging if BigQuery isn’t your DWH solution.
CDW Research Hub
APRIL 20, 2020
Snowflake, a data warehouse built specifically for the cloud, is one popular option. Snowflake helps eliminate many of the common issues data professionals face because it supports structured and semi-structured data, scales massive concurrency without limit, and boasts secure, live data sharing.
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