Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s. Security: It must serve data throughout a system.

Data Governance 86

Data Governance Metadata Data-driven Enterprise 86

Ontotext

FEBRUARY 12, 2024

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

Anmut

OCTOBER 29, 2020

As a result, concerns of data governance and data quality were ignored. The direct consequence of bad quality data is misinformed decision making based on inaccurate information; the quality of the solutions is driven by the quality of the data. COVID-19 exposes shortcomings in data management.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

bridgei2i

MARCH 11, 2021

With improved data cataloging functionality, their systems can become responsive. It’ll become easier to store metadata (data lakes, warehouses, data quality systems, etc.) Over time, as more data is constantly fed to the responsive system, ML algorithms improve their efficiency. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

CIO Business Intelligence

MARCH 29, 2022

Lowering the entry cost by re-using data and infrastructure already in place for other projects makes trying many different approaches feasible. Fortunately, learning-based projects typically use data collected for other purposes. . You have data but don’t use it. Why does valuable data so often go unused?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

Peter James Thomas

AUGUST 29, 2018

My role encompasses being the business driver for the data platform that we are rolling out across the organisation and its success in terms of the data going onto the platform and the curation of that data in a governed state, depending on the consumer requirements.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. We had Julia Lane talking about Coleridge Initiative and the work on Project Jupyter to support metadata and data governance and lineage. How can you trace that all the way back into the data collection? You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Andrew White

JANUARY 9, 2022

– We see most, if not all, of data management being augmented with ML. Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration.

Analytics 64

Analytics Measurement Data-driven Modeling 64

CIO Business Intelligence

NOVEMBER 22, 2022

Data fabric is an architecture that enables the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

erwin

MARCH 4, 2021

Like CCPA, the Virginia bill would give consumers the right to access their data, correct inaccuracies, and request the deletion of information. Virginia residents also would be able to opt out of data collection.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. As you would guess, maintaining context relies on metadata.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

O'Reilly on Data

DECEMBER 19, 2018

Data management isn’t limited to issues like provenance and lineage; one of the most important things you can do with data is collect it. Given the rate at which data is created, data collection has to be automated. How do you do that without dropping data? Toward a sustainable ML practice.

Machine Learning 275

Machine Learning Software Metadata Testing 275

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

datapine

JANUARY 31, 2022

As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Alation

FEBRUARY 17, 2023

Some data seems more analytical, while other is operational (external facing). We recommend identifying the data sources and tables that need to be considered to be governed, establishing the governance owner & data quality details, and saving those details in the catalog. Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

DataKitchen

JUNE 24, 2021

Bergh added, “ DataOps is part of the data fabric. You should use DataOps principles to build and iterate and continuously improve your Data Fabric. Automate the data collection and cleansing process. Education is the Biggest Challenge. “We Take a show-me approach.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Alation

DECEMBER 15, 2021

Modern business is built on a foundation of trusted data. Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

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.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

NOVEMBER 11, 2021

Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance? Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

Alation

MARCH 17, 2021

According to the Forrester Wave: Machine Learning Data Catalogs, Q4 2020 , “Alation exploits machine learning at every opportunity to improve data management, governance, and consumption by analytic citizens. MLDCs improve upon traditional metadata management systems by injecting intelligence. Tracking and Scaling Data Lineage.

Machine Learning 52

Machine Learning Metadata Data Governance Data Quality 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Quality Data Governance Data-driven 130