CIO Business Intelligence

DECEMBER 19, 2023

Create these six generative AI workstreams CIOs should document their AI strategy for delivering short-term productivity improvements while planning visionary impacts. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

IT 136

IT Risk Cost-Benefit Risk Management 136

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

erwin

OCTOBER 17, 2019

it ensures not only access to proper documentation but also current, updated information. The Regulatory Rationale for Integrating Data Management & Data Governance. Data security/risk management. EA should be commonplace in data security planning. Data governance.

Enterprise 106

Enterprise Digital Transformation Data Governance Risk Management 106

erwin

AUGUST 20, 2020

As a practice, EA involves the documentation, analysis, design and implementation of an organization’s assets and structure. With an enterprise architecture management suite (EAMS) , an organization can define and document its structure to more effectively determine how to achieve its goals. Reduced risks and costs.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

JUNE 14, 2019

Its past successes – and future potential – are well documented, chronicled in the billion-dollar valuations of the frontrunners in the practice. Four main areas in retail demonstrate digital transformation, with a healthy data governance initiative driving them all. Data can tell you. Risks come with any investment.

Digital Transformation 111

Digital Transformation Data Governance Risk Data-driven 111

erwin

APRIL 29, 2020

In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates. Business terms and data policies should be implemented through standardized and documented business rules.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Cloudera

AUGUST 12, 2021

In a 2021 white paper titled “Data Excellence: Transforming manufacturing and supply systems“ written by the World Economic Forum and the Boston Consulting Group, it documented that 75% of executives interviewed believed that advanced analytics in manufacturing was more important today than three years ago. Risk Management.

Data-driven 107

Data-driven Manufacturing Insurance Risk Management 107

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

Octopai

JULY 9, 2020

By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed. That increase can manage huge endeavors, such as migrations, error location, and new data governance integrations which then become “routine” operations.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. Data Center Consolidation. Application Portfolio Management. Data Governance (knowing what data you have and where it is). Digital Transformation. Compliance/Legislation. Artificial Intelligence. Mergers and Acquisitions.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

Alation

OCTOBER 26, 2021

Although operations and sales departments tend to champion the use of data for business insight 3 , we’ve found that finance departments are often the first adopters of the Alation Data Catalog within an organization. This is because accurate data is “table stakes” for finance teams. What is most critical to the business?

Finance 52

Finance Data Transformation Enterprise Metrics 52

bridgei2i

NOVEMBER 25, 2020

This will also minimize the risk involved in the process. When it comes to using it in an enterprise, semantic search is used to identify the knowledge graphs and help find the data the employees are looking for. It streamlines data flow throughout the enterprise and brings flexibility to the system.

Enterprise 52

Enterprise Data mining Consulting Risk Management 52

Alation

MARCH 14, 2023

Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision. Creating a clear process with documented steps will help.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

IBM Big Data Hub

JULY 7, 2023

Create an incident response plan , a written document that details how you will respond before, during and after a suspected or confirmed security threat. Such mobile devices increase risk because they are authenticated and authorized in different ways and introduce new endpoints that need protection from cyber threats.

Risk 40

Risk Data Governance Data Lake Data-driven 40

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

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

NOVEMBER 18, 2021

The variety of formats, unstructured nature, and dispersed location of these documents present several challenges for critical business decisions. To enable faster and easier access to millions of documents, ExxonMobil combined domain specific knowledge and a combination of Cloudera tools with cloud services. Data for Good.

Data Lake 75

Data Lake Cost-Benefit Digital Transformation Risk 75

erwin

APRIL 21, 2020

One of the biggest lessons we’re learning from the global COVID-19 pandemic is the importance of data, specifically using a data catalog to comply, collaborate and innovate to crisis-proof our businesses. Give guidance to governments, health professionals and the public. Clearly Document Data Policies and Rules.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

One of the biggest lessons we’re learning from the global COVID-19 pandemic is the importance of data, specifically using a data catalog to comply, collaborate and innovate to crisis-proof our businesses. Give guidance to governments, health professionals and the public. Clearly Document Data Policies and Rules.

Measurement 96

Measurement Sales Data Governance Metadata 96

erwin

OCTOBER 24, 2019

Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Grooper

OCTOBER 23, 2019

Lack of competitiveness or business losses seem to be the main drivers to becoming more proactive with data governance and management. What you’re shooting for is enterprise-wide information governance. Responsibility for managing your company’s data must be clearly defined and supported. Governance.

Metrics 59

Metrics Measurement Strategy Optimization 59

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. They can govern the implementation with a documented business case and be responsible for changes in scope. On the flip side, document everything that isn’t working. Develop a “Data Dictionary”.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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 79

Management Risk Measurement Optimization 79