Alation

JULY 6, 2021

Common Data Governance Challenges. Every enterprise runs into data governance challenges eventually. Issues like data visibility, quality, and security are common and complex. Data governance is often introduced as a potential solution. And one enterprise alone can generate a world of data.

Data Governance 52

Data Governance Metadata Data Quality Risk 52

FineReport

MAY 31, 2023

Data Quality and Consistency : Maintaining data quality and consistency is essential for reliable financial insights. Inaccurate or inconsistent data can lead to erroneous conclusions and decisions. Data Security : Financial data is highly sensitive and requires robust security measures.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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. to Data Governance 2.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

CIO Business Intelligence

JANUARY 24, 2024

“IT leaders should establish a process for continuous monitoring and improvement to ensure that insights remain actionable and relevant, by implementing regular review cycles to assess the effectiveness of the insights derived from unstructured data.” This type of environment can also be deeply rewarding for data and analytics professionals.”

Data Strategy 135

Data Strategy Strategy Unstructured Data Data Governance 135

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 307

Enterprise Deep Learning Data Governance Risk 307

erwin

APRIL 18, 2019

Data governance , thankfully, provides a framework for compliance with either or both – in addition to other regulatory mandates your organization may be subject to. CCPA Compliance Requirements vs. Publicly available personal information (federal, state and local government records). Data Governance for Regulatory Compliance.

Data Governance 81

Data Governance Metadata Data-driven Data Collection 81

Alation

JULY 15, 2022

And, while change at large organisations is tough, data leaders would be wise to reframe such transformations as business opportunities rather than burdens. Clearly, using private Facebook data collected in a nefarious manner to sway political elections is not ethical. Ethics in Regulation.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

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

Alation

SEPTEMBER 1, 2022

The goal of this report is to “evaluate software that provides a large number of different users with the agility they need to use data in an effective and efficient way.” By definition, a data intelligence platform must serve a wide variety of user types and use cases – empowering them to collaborate in one shared space.

Reporting 52

Reporting Metadata Data Governance Interactive 52

IBM Big Data Hub

FEBRUARY 23, 2024

Second, a comprehensive inventory makes it easier to comply with user requests to share, update, or delete their data. Children’s data cannot be processed without parental consent, and organizations need mechanisms to verify the ages of data subjects and the identities of their parents. Consents cannot be bundled, either.

Measurement 78

Measurement Risk Data Collection Data Processing 78

Alation

OCTOBER 12, 2021

Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Yet the explosion of data collection and volume presents new challenges. Like many, the team at Cbus wanted to use data to more effectively drive the business. The third challenge was around trusting the data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Sisense

JULY 6, 2020

EDM covers the entire organization’s data lifecycle: It designs and describes data pipelines for each enterprise data type: metadata, reference data, master data, transactional data, and reporting data. Data governance is the foundation of EDM and is directly related to all other subsystems.

Enterprise 98

Enterprise Management Data Architecture Strategy 98

datapine

FEBRUARY 22, 2022

Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Think of security, privacy, and compliance.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

Metadata 64

Metadata Data Governance Dashboards Software 64

erwin

APRIL 21, 2020

So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance. What’s the best way to organize data and ensure it is supported by business policies and well-defined, governed systems, data elements and performance measures? Put border controls in place.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance. What’s the best way to organize data and ensure it is supported by business policies and well-defined, governed systems, data elements and performance measures? Put border controls in place.

Measurement 96

Measurement Sales Data Governance Metadata 96

IBM Big Data Hub

JANUARY 22, 2024

Schools, hospitals and government agencies all fall under GDPR authority. The only data processing activities exempt from the GDPR are national security or law enforcement activities and purely personal uses of data. Useful definitions The GDPR uses some specific terminology.

Measurement 83

Measurement Risk Data Processing Data Collection 83

Octopai

AUGUST 26, 2021

The entry features the data asset description (i.e. the stalk of barley symbol and the circular numeral signs) and the data owner (i.e. This data catalog didn’t need automation. It was perfectly reasonable for an individual to manually manage a Sumerian data collection (especially if you paid him enough barley).

Metadata 52

Metadata Cost-Benefit Data Collection Reporting 52

Jet Global

MARCH 13, 2019

Automation will empower rapidly scaling businesses to address data science shortcomings by applying algorithms to existing data—definitely one of the primary use cases for AI, finally realized in the coming year. Data Governance. AI vs. BI for Business, What Do You Need? READ BLOG POST. Natural Language Processing.

Business Intelligence 85

Business Intelligence Data Science Software Enterprise 85

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

FEBRUARY 13, 2020

A Data Catalog is a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses. Improved data efficiency.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Jet Global

DECEMBER 17, 2021

For example, the research finds that nearly half (48%) of finance organizations spend too much time on closing the books in reporting entities, and a similar percentage spend too much time on subsequent steps, such as, data collection, validation, and submission of data to the corporate center.

Reporting 52

Reporting Management Recreation/Entertainment Finance 52

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Data governance is a key use case of the modern data stack.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Andrew White

JANUARY 9, 2022

Could you precise to which complementary research you mentioned when you talked about a data governance survey ? – Here is the one I mentioned during the webinar: The State of Data and Analytics Governance Is Worse Than You Think. – Data (and analytics) governance remains a challenge.

Analytics 64

Analytics Measurement Modeling Data-driven 64