Cloudera

AUGUST 31, 2021

The Accenture Smart Data Transition Toolkit is also tightly integrated with Cloudera Data Platform for cloud data management and Cloudera Shared Data Experiences for secure, self-service analytics. These schemas will be created based on its definitions in existing legacy data warehouses.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Rockset

MARCH 1, 2023

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

Data Ingestion 144

Data Ingestion Database Architecture Cloud Storage 144

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management.

Raw Data 70

Raw Data Data Business Intelligence High Quality Data 70

ProjectPro

JANUARY 31, 2023

Define Big Data and Explain the Seven Vs of Big Data. Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. How can AWS solve Big Data Challenges?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Monte Carlo

OCTOBER 5, 2023

So, in order for your company to uncover the true value of its data, you must take a structured approach to data quality. That’s where data quality standards come into play. Data freshness (aka data timeliness) means your data should be up-to-date and relevant to the timeframe of analysis. name@domain.com).

Government 52

Government Data Governance Data Datasets 52

ProjectPro

AUGUST 21, 2015

Core components of a Hadoop application are- 1) Hadoop Common 2) HDFS 3) Hadoop MapReduce 4) YARN Data Access Components are - Pig and Hive Data Storage Component is - HBase Data Integration Components are - Apache Flume, Sqoop, Chukwa Data Management and Monitoring Components are - Ambari, Oozie and Zookeeper.

Hadoop 40

Hadoop Big Data Metadata Unstructured Data 40