Cask Hydrator: Self Service Data Lakes on Hadoop

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.

whitePaper | August 10, 2022

Connected Data, though used synonymously with Big Data, is carefully created and curated for storage and reference during the customer’s lifetime. As we already know, enterprises need to carefully build and store Big Data to avoid creating a data swamp. Connected Data goes a step ahead of Big Data. It is customer-specific data built in a context-sensitive framework to ensure a 360-degree view of the customer profile, purchasing habits, preferences, etc., at a glance.

whitePaper | August 25, 2022

Rubrik is the world’s first Cloud Data Management platform that delivers data protection, search, analytics, and copy data management to hybrid cloud enterprises.

whitePaper | December 22, 2022

The key objective of setting up data mesh or data fabric architecture is to enable the availability of quality data in a timely fashion to the right people in the right format. A data fabric is an architecture framework and a set of data services that provide frictionless data capabilities across a choice of endpoint applications or services spanning hybrid or multi-cloud and on-premises, by using rich metadata foundation and artificial intelligence/machine learning (AI/ML) automation.

whitePaper | January 11, 2023

The world of master data management (MDM) is a complicated place to navigate and its native speakers use a language sometimes only they themselves understand. It is packed with complex descriptions, esoteric lingo and acronyms.

whitePaper | June 27, 2023

Data mesh is an innovative approach to data management that offers a solution to the most common challenges organizations face when dealing with large-scale data management. Data mesh concept consists of four key principles for large-scale data management in a multi-tiered, multi-domain organizational structure: domainoriented ownership, data as product, federated computational governance and a self-service data platform. These all promote a more agile, efficient and scalable data architecture. However, one of the central challenges to implementing data mesh is designing decentralized governance mechanisms that align with its core principles.