IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Alation

FEBRUARY 13, 2020

By leveraging Google-like smart search to find data assets; using automation and self-learning instead of burdening people with the need to manually update metadata in multiple places; and ensuring that metadata is maintained by the whole data community and is not dependent on a centralized IT team.

Machine Learning 52

Machine Learning Data Analytics Analytics Metadata 52

AWS Big Data

APRIL 25, 2024

This approach allows the team to process the raw data extracted from Account A to Account B, which is dedicated for data handling tasks. This makes sure the raw and processed data can be maintained securely separated across multiple accounts, if required, for enhanced data governance and security. secretsmanager ).

Metadata 72

Metadata Data Processing Management Testing 72

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. SECURITY AND GOVERNANCE LEADERSHIP. Data for Enterprise AI: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning.

Digital Transformation 65

Digital Transformation Machine Learning Optimization Data Lake 65

AWS Big Data

OCTOBER 4, 2023

Collaboration – Analysts, data scientists, and data engineers often own different steps within the end-to-end analytics journey but do not have an simple way to collaborate on the same governed data, using the tools of their choice.

Metadata 98

Metadata Data Lake Publishing Data Governance 98

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

Data Architecture 65

Data Architecture Metadata Data Lake Snapshot 65

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. 2 “Exposing The Data Mesh Blind Side ” Forrester.

Management 88

Management Metadata Data Architecture Data Lake 88

Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. Data Governance and Data Security.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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.) And that makes sense.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape.

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Frequent table maintenance needs to be performed to prevent read performance from degrading over time.

Data Lake 111

Data Lake Metadata Optimization Statistics 111

Cloudera

FEBRUARY 11, 2019

The former sees growing investment in data analytics to become data-driven (45% of organizations expect to increase their spending in this area) while the latter is fueled by disruptive technology and the adoption of AI (41% of organizations name it as their game changer). Governing digital transformation.

Digital Transformation 56

Digital Transformation Data Governance Data Warehouse Data-driven 56

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Andrew White

JANUARY 11, 2021

Governance. Risk Management (most likely within context of governance). Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. See recorded webinars: Emerging Practices for a Data-driven Strategy. Link Data to Business Outcomes. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 87

Data Lake Data Warehouse B2B Data-driven 87

Ontotext

FEBRUARY 12, 2024

A centralized data engineering team focuses on building a governed self-serviced infrastructure, while domain teams use the services to build full-stack data products. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. This ties into the failure of data governance and MDM (see first item in this list).

Analytics 68

Analytics Metadata Data Governance Management 68