Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

erwin

APRIL 15, 2020

In our businesses, it is vital that we work to develop a deeper understanding of the sources, methods and quality of incoming third-party data. This deeper understanding will help us make better decisions about the risks and rewards of using that external data. Data Governance Methods for Data Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

Anmut

JUNE 9, 2023

Data governance roles are positions within an organisation that ensure data is managed and used effectively. Just like companies use corporate governance to run the business and make the most of their assets, these roles are critical for managing data as an asset and maximising its value.

Data Governance 52

Data Governance Cost-Benefit Metadata Strategy 52

Alation

APRIL 25, 2023

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

APRIL 25, 2023

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Octopai

JUNE 19, 2023

Including them in the design and implementation process ensures that the data catalog meets their needs, and requirements, and aligns with business goals. Establish Data Governance Policies A crucial part of implementing a data catalog is establishing robust data governance policies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

erwin

JUNE 26, 2020

These fragmented data environments make data governance a challenge since business stakeholders, data analysts and other users are unable to discover data or run queries across an entire data set. This also diminishes the value of data as an asset. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

erwin

JUNE 22, 2020

Earlier this year, erwin released its 2020 State of Data Governance and Automation (DGA) report. About 70 percent of the DGA report respondents – a combination of roles from data architects to executive managers – say they spend an average of 10 or more hours per week on data-related activities.

Metadata 105

Metadata Data Governance Digital Transformation Measurement 105

Octopai

APRIL 11, 2021

The Digital Charter covers aspects of digital policy ranging from increased digital access for Canadians to measures that protect democracy and accurately identify hate speech. A key system to smooth out the bumps is a metadata management platform that includes automated data discovery and automated data lineage.

Metadata 52

Metadata Management Measurement IT 52

CDW Research Hub

MAY 29, 2019

Data governance helps organizations manage their information and answer questions about business performance, allowing them to better understand data, and govern it to mitigate compliance risks and empower information stakeholders. Checklist: Building an Enterprise Data Governance Program.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

O'Reilly on Data

JANUARY 29, 2019

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. In order to have a longstanding AI and ML practice, companies need to have data infrastructure in place to collect, transform, store, and manage data.

Deep Learning 209

Deep Learning Machine Learning Data Science Metadata 209

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance. Data Governance 2.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Alation

MAY 12, 2023

At Alation, one of our core values is to measure success through customer impact. Data Governance And while other companies may say they have a data governance solution, Alation’s proven track record in data governance has earned us the Snowflake Data Governance Partner of the Year for two years running.

Metadata 52

Metadata Data Governance Data-driven Sales 52

Cloudera

JULY 17, 2023

At lower levels of grain our measurements are data-driven and automated, but at the macro level we prefer to apply some subjectivity (of course our weightings will differ from yours as we are on a different journey). Our data and analytics leaders meet monthly to evaluate our health improvement and log subjective measures.

Scorecard 71

Scorecard Measurement Dashboards Data-driven 71

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Alation

MAY 12, 2023

At Alation, one of our core values is to measure success through customer impact. Data Governance And while other companies may say they have a data governance solution, Alation’s proven track record in data governance has earned us the Snowflake Data Governance Partner of the Year for two years running.

Metadata 40

Metadata Data Governance Data-driven Sales 40

BI-Survey

AUGUST 22, 2023

It is about a focus on data products and the decentralized creation of and responsibility for data products in the line of business, which are based on a self-service analytics infrastructure and federated data governance with a high degree of automation. Management summary Should business domains own data products?

Measurement 52

Measurement Data Governance Data-driven Dashboards 52

IBM Big Data Hub

APRIL 10, 2023

To further the above, organizations should have the right foundation that consists of a modern data governance approach and data architecture. It’s becoming critical that organizations should adopt a data architecture that supports AI governance.

Strategy 86

Strategy Data Architecture Cost-Benefit Reporting 86

Cloudera

MAY 2, 2022

As digital transformation accelerates, and digital commerce increasingly becomes the dominant form of all commerce, regulators and governments around the world are recognizing the increased need for consumer protections and data protection measures.

Metadata 106

Metadata Data Architecture Digital Transformation Finance 106

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

Alation

JANUARY 19, 2023

The words “ data governance ” and “fun” are seldom spoken together. The term data governance conjures images of restrictions and control that result in an uphill challenge for most programs and organizations from the beginning. Or they are spending too much time preparing the data for proper use.

Data Governance 94

Data Governance IT Metadata Recreation/Entertainment 94

Alation

MARCH 11, 2022

A data catalog with a Behavioral Analysis Engine will measure human behavior around data to locate your most valuable and actionable data. This data about data, AKA metadata , is an essential layer of your new meshy fabric. Tip 3: Never, ever skip data governance.

Metadata 52

Metadata Data Governance ROI Data Quality 52

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. Your analytics strategy applies to the wider organizational needs, not just C360.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

AWS Big Data

JULY 28, 2023

The following sections discuss a few commonly referenced architecture patterns, best practices, and options supported by Amazon Redshift to support your data subject’s GDPR right to be forgotten request in your organization. Tags provide metadata about resources at a glance.

Snapshot 83

Snapshot Metadata Measurement Data Warehouse 83

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 88

Data Architecture Risk Management Risk Management 88

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

Octopai

APRIL 4, 2022

When you need to keep careful track of what’s happening to your data, data lineage for healthcare is your ally. Data lineage maps out the journey of any data asset or data point based on the metadata in healthcare systems. Complex Times Call for Complex Measures . What other systems did that affect?

Metadata 92

Metadata Reporting Visualization Insurance 92

IBM Big Data Hub

JANUARY 5, 2023

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Data Wrangling and Feature Engineering.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

MARCH 22, 2022

DataOps requires an array of technology to automate the design, development, deployment, and management of data delivery, with governance sprinkled on for good measure. The table details are extracted from the IDF pipeline information, which then syncs details like column, table, business, and technical metadata.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Octopai

JULY 9, 2020

When conducted manually, however, which has tended to be the normal mode of operation before companies discovered automation – or machine learning data lineage solutions, data lineage can be extremely tedious and time-consuming for BI & Analytics teams. A key piece of legislation that emerged from that crisis was BCBS-239.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86