CIO Business Intelligence

FEBRUARY 16, 2023

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

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

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. DataOps is critically dependent on robust governance and cataloging capabilities. Transparency is key.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. But there are only so many data engineers available in the market today; there’s a big skills shortage. Let’s take data privacy as an example.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 83

Cost-Benefit Metadata Optimization Management 83

Smarten

AUGUST 4, 2023

If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization. Machine learning capability determines the best techniques, and the best fit transformations for data so that the outcome is clear and concise.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59