Rockset
JULY 9, 2019
One of the main hindrances to getting value from our data is that we have to get data into a form that’s ready for analysis. Consider the hoops we have to jump through when working with semi-structured data, like JSON, in relational databases such as PostgreSQL and MySQL. It sounds simple, but it rarely is.
Knowledge Hut
MARCH 27, 2024
Use Cases Ideal for applications requiring structured storage and retrieval of data, such as in business or web development. Essential in programming for tasks like sorting, searching, and organizing data within algorithms. Supports complex query relationships and ensures data integrity.
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Knowledge Hut
JUNE 16, 2023
Data preparation: Because of flaws, redundancy, missing numbers, and other issues, data gathered from numerous sources is always in a raw format. After the data has been extracted, data analysts must transform the unstructured data into structured data by fixing data errors, removing unnecessary data, and identifying potential data.
Silectis
JANUARY 3, 2021
Data Science Data science is a practice that uses scientific methods, algorithms and systems to find insights within structured and unstructured data. Data Visualization Graphic representation of a set or sets of data. Data Warehouse A storage system used for data analysis and reporting.
Rockset
OCTOBER 20, 2021
Let’s walk through an example workflow for setting up real-time streaming ELT using dbt + Rockset: Write-Time Data Transformations Using Rollups and Field Mappings Rockset can easily extract and load semi-structured data from multiple sources in real-time. PostgreSQL or MySQL). S3 or GCS), NoSQL databases (e.g.
ProjectPro
FEBRUARY 16, 2023
To analyze big data and create data lakes and data warehouses , SQL-on-Hadoop engines run on top of distributed file systems. The SQL-on-Hadoop platform combines the Hadoop data architecture with traditional SQL-style structured data querying to create a specific analytical application tool.
ProjectPro
SEPTEMBER 26, 2014
The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.
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