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

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

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

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 40

Data Governance ROI Risk Management Metadata 40

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

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

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

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.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

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

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 363

Marketing Experimentation Metrics Testing 363

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

NOVEMBER 15, 2021

We implemented policy bots that monitor specific conditions in the metadata related to the policies and standards. We used our ability to bi-directionally sync with Snowflake row-based access control, masking policies, and entitlements to relate those to higher-level governance policies, standards, and the discovery of sensitive data.

Management 52

Management Testing Metadata Consulting 52

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

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. Data mapping involves identifying and documenting the flow of personal data in an organization.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. 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.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

erwin

JUNE 27, 2019

Data modeling, quite simply, describes the process of discovering, analyzing, representing and communicating data requirements in a precise form called the data model. There’s an expression: measure twice, cut once. Empowering of end-user BI/analytics by data source discovery, analysis and integration. .

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

erwin

APRIL 21, 2020

By combining physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals, you can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

Think about the pandemic itself and the numerous global entities involved in identifying it, tracking its trajectory, and providing guidance to governments, healthcare systems and the general public. One example is the European Union (EU) Open Data Portal , which is used to document, catalog and govern EU data related to the pandemic.

Measurement 96

Measurement Sales Data Governance Metadata 96

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. And that makes sense.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

Laminar Security

SEPTEMBER 18, 2023

I’ve previously discussed the risk of shadow data (those data stores you didn’t even know you had), and the team specifically dove into how versioning (a feature used to protect from accidental deletion) can unintentionally create shadow data. There is another class of shadow data that’s caused intentionally by data backups.

Risk 128

Risk Testing Data Governance Metadata 128

IBM Big Data Hub

JANUARY 9, 2024

Currently, no standardized process exists for overcoming data ingestion’s challenges, but the model’s accuracy depends on it. Increased variance: Variance measures consistency. Insufficient data can lead to varying answers over time, or misleading outliers, particularly impacting smaller data sets.

Enterprise 72

Enterprise Data Integration Data Quality Contextual Data 72

AWS Big Data

JANUARY 22, 2024

Discussions with users showed they were happier to have faster access to data in a simpler way, a more structured data organization, and a clear mapping of who the producer is. A lot of progress has been made to advance their data-driven culture (data literacy, data sharing, and collaboration across business units).

Data-driven 86

Data-driven Advertising Metadata Data Architecture 86

IBM Big Data Hub

APRIL 11, 2024

Key themes and concerns are emerging, however government agencies must get ahead of the game by evaluating their agency-specific priorities and processes. Compliance with official policies through auditing tools and other measures is merely the final step.

Risk 74

Risk Consulting Modeling Data Processing 74

Domino Data Lab

AUGUST 8, 2019

In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. First and foremost: there’s substantial overlap between what the scientific community is working toward for scholarly infrastructure and some of the current needs of data governance in industry. Sci Foo 2019.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

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

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. In other words, D&A plays a key role in the foundational measuring angle. Is there a good map that shows the connections between data, advanced analytics, digital, innovation, etc. – Yes and no. This was from 2020.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

JANUARY 17, 2023

Data literacy — Employees can interpret and analyze data to draw logical conclusions; they can also identify subject matter experts best equipped to educate on specific data assets. Data governance is a key use case of the modern data stack. Who Can Adopt the Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Grooper

OCTOBER 23, 2019

By measuring performance, they drive improvements through necessary process and workflow changes. It simply takes the right resources and a measured approach to get there. Most companies today are more reactive to information governance. As Peter Drucker so famously said, “If you can’t measure it, you can’t improve it.”

Metrics 59

Metrics Measurement Strategy Optimization 59

Alation

DECEMBER 15, 2021

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 requires a system.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you have proper data management without establishing a formal data governance program?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

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. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Governance Data Quality Data-driven 130

AWS Big Data

AUGUST 14, 2023

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.

Management 80

Management Risk Measurement Optimization 80

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