Jet Global

JULY 2, 2019

Ungoverned or uncatalogued data can leave businesses vulnerable both in terms of data quality (and organizational trust in that data), as well as in terms of security, regulatory, and compliance risks. Build your Business Intelligence Infrastructure on a Solid Foundation.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

NOVEMBER 16, 2023

Through Amazon Redshift in-memory result set caching and compilation caching, workloads ranging from dashboarding to visualization to business intelligence (BI) that run repeat queries experience a significant performance boost. A predicate consists of a metric, a comparison condition (=, ), and a value.

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

DataKitchen

OCTOBER 11, 2021

Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. While implementing a DataOps solution, we make sure that the pipeline has enough automated tests to ensure data quality and reduce the fear of failure. Monitoring Job Metadata. Priyanjna Sharma.

Testing 152

Testing Metadata Dashboards Statistics 152

Alation

JULY 19, 2022

A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms. How Data Catalogs Help Data Scientists Ask Better Questions.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

MAY 31, 2023

American Family Insurance: Governance by Design – Not as an Afterthought Who: Anil Kumar Kunden , Information Standards, Governance and Quality Specialist at AmFam Group When: Wednesday, June 7, at 2:45 PM Why attend: Learn how to automate and accelerate data pipeline creation and maintenance with data governance, AKA metadata normalization.

Data Governance 52

Data Governance Insurance Metadata Data-driven 52

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 88

Data Lake Analytics Snapshot Optimization 88

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Experience the power of Business Intelligence with our 14-days free trial! Why Is Business Intelligence So Important?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. Business intelligence reports. The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? One is data quality, cleaning up data, the lack of labelled data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

APRIL 12, 2022

CDOs have a mandate across the data value chain, across that whole life cycle of data. Data governance also extends across that life cycle. It’s not just about security or privacy or ensuring data quality; it’s also ensuring the right people can access it and use it to deliver value to the organization.”.

Data Quality 52

Data Quality Data Governance Metrics Data Strategy 52

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. Provide and keep up to date with technical metadata for loaded data.

Dashboards 111

Dashboards Publishing Data-driven Cost-Benefit 111

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

AWS Big Data

AUGUST 14, 2023

Goals of DPPM The goals of DPPM can be summarized as follows: Protect value – DPPM protects the value of the organizational data strategy by developing, implementing, and enforcing frameworks to measure the contribution of data products to organizational goals in objective terms. Monitoring and Event Management X X.

Management 79

Management Risk Measurement Optimization 79