AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale.

Snapshot 86

Snapshot Data Lake Testing Strategy 86

CIO Business Intelligence

JUNE 9, 2022

In these instances, data feeds come largely from various advertising channels, and the reports they generate are designed to help marketers spend wisely. All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Of course, marketing also works. Survey CTO.

Management 137

Management Advertising Data Lake Sales 137

CIO Business Intelligence

SEPTEMBER 22, 2023

What are the benefits of data management platforms? Modern, data-driven marketing teams must navigate a web of connected data sources and formats. All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Of course, marketing also works.

Management 97

Management Advertising Data Lake Sales 97

Cloudera

FEBRUARY 8, 2024

The snapshotId of the source tables involved in the materialized view are also maintained in the metadata. Incremental and full rebuild of materialized view We will insert rows into the base table and examine how the materialized view can be updated to reflect the new data. Furthermore, it is partitioned on the d_year column.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

Alation

APRIL 18, 2023

On the contrary, data profiling today describes an automated process, where a data user can “point and click” to return key results on a given asset, like aggregate functions, top patterns, outliers, inferred data types, and more. This can include rules for data completeness, consistency, accuracy, and validity.

IT 52

IT Metadata Data Quality Data Governance 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

Domino Data Lab

AUGUST 8, 2019

I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure. The gist is, leveraging metadata about research datasets, projects, publications, etc., It’s a quick way to clear the room. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Andrew White

JANUARY 11, 2021

Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? You cannot get away from a formalized delivery capability focused on regular, scheduled, structured and reasonably governed data. Data lakes don’t offer this nor should they. E.g. Data Lakes in Azure – as SaaS.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52