IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. There are several styles of data integration.

Cost-Benefit 72

Cost-Benefit Data Integration Data Architecture Manufacturing 72

Cloudera

SEPTEMBER 7, 2023

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Systematize governance. Create core feedback mechanisms.

Insurance 79

Insurance Risk Data-driven Finance 79

Cloudera

APRIL 14, 2021

Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. . Precisely Data Integration, Change Data Capture and Data Quality tools support CDP Public Cloud as well as CDP Private Cloud. Why should technology partners care about CDE? References: [link].

Data Warehouse 79

Data Warehouse Data Processing Data Quality Machine Learning 79

AWS Big Data

JULY 20, 2023

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Modeling Metrics 52

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. But I would search on our web site for AI and mid-size enterprise; or ask Anthony Mullen who leads our AI research in our data and analytics team. Can you remind where we can find the mentioned blog?

Analytics 64

Analytics Measurement Modeling Data-driven 64

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

datapine

MAY 17, 2021

If you have multiple databases from different touchpoints, you should look for a tool that will allow data integration no matter the amount of information you want to include. Besides connecting the data, the discovery tool you choose should also support working with big amounts of data. Why are they important?

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

Jet Global

OCTOBER 26, 2023

If your finance team is using JD Edwards (JDE) and Oracle E-Business Suite (EBS), it’s like they rely on well-maintained and accurate master data to drive meaningful insights through reporting. For these teams, data quality is critical. Ensuring that data is integrated seamlessly for reporting purposes can be a daunting task.

Data Quality 52

Data Quality Reporting Operational Reporting Finance 52