Alation

MARCH 22, 2022

In fact, DataOps (and its underlying foundation, Data Fabric ), has ranked as a top area of inquiry and interest with analysts over the past twelve months. DataOps requires an array of technology to automate the design, development, deployment, and management of data delivery, with governance sprinkled on for good measure.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Alation

JUNE 28, 2022

The real challenge lies in getting people to access, manage, and search for it appropriately. This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Who’s starring in it.

Metadata 52

Metadata Management Data Governance Machine Learning 52

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. The What: Data Governance Defined. Data governance has no standard definition.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. A modern data architecture is critical in order to become a data-driven organization.

Technology 78

Technology Data-driven Machine Learning Sales 78

Alation

AUGUST 11, 2022

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

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 82

Cost-Benefit Metadata Optimization Management 82

Alation

JANUARY 17, 2023

Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Octopai

NOVEMBER 23, 2020

Naturally, this will produce a massive growth in data management needs. Particularly in financial services, each company’s data team will have significant work to do to keep up with these developments and this is on top of the regulatory challenges that they already face on a daily basis.

Metadata 54

Metadata Enterprise Business Intelligence Data Governance 54

Octopai

JANUARY 19, 2021

This is done by visualizing the Azure Data Factory pipelines’ full column-level with source-to-target traceability through different data transformations at the most detailed level. Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes.

Metadata 52

Metadata ROI Optimization Data Quality 52

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere accesses and integrates both SAP and non-SAP data sources into end-users’ data flows, including on-prem data warehouses, cloud data warehouses and lakehouses, relational databases, virtual data products, in-memory data, and applications that generate data (such as external API data loads).

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

DataKitchen

JANUARY 23, 2023

Data lineage can also be used for compliance, auditing, and data governance purposes. DataOps Observability Five on data lineage: Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Ontotext

FEBRUARY 12, 2024

This promotes data autonomy and enables decision-making about data domains without centralized gatekeepers. It also breaks down the code and data monolith and distributes it across the domain teams, which results in better management and scalability. by building data products with domain owners.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 66

Data Lake Metadata Cost-Benefit Data Warehouse 66

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 85

Data Lake Data Warehouse Data-driven B2B 85

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 14, 2024

Mastering Data: Effectively Manage Your Data Download Now How Jet Analytics Enhances Microsoft Fabric Jet Analytics from insightsoftware is a complete data preparation, automation and modeling solution that enables Microsoft Dynamics customers to accelerate Dynamics ERP-ready BI projects without requiring specialist skills.

Analytics 52

Analytics Management Reporting Enterprise 52