Monte Carlo

JULY 10, 2023

The same is true with data. If all the information in a data set is accurate and precise, but key values or tables are missing, your analysis won’t be effective. That’s where the definition of data completeness comes in. Be sure to use random sampling to select representative subsets of your data.

Data Collection 40

Data Collection Data Governance Government Data 40

Ascend.io

JUNE 8, 2023

Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications. This multitude of sources often causes a dispersed, complex, and poorly structured data landscape. Data stewards are thus the best contributors to the content of data catalogs.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Ascend.io

JULY 19, 2023

Establish clear data governance policies. The policies should outline rules and standards for data. These should be explicit and prescriptive, addressing the 5 aspects below: Domain and business key definitions: Clearly define your business keys and the domains they belong to. Develop a data product lifecycle framework.

Data Governance 40

Data Governance Government Metadata Data 40

Monte Carlo

JANUARY 25, 2023

That being said, it tends to be much easier to reprocess data in the data warehouse when we do find bad records, whereas that might not be possible in a streaming environment. Definition of data contracts Similar to contracts in production services, contracts in the warehouse should be implemented in code and version controlled.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40