Smart Data Collective

DECEMBER 21, 2022

This market is growing as more businesses discover the benefits of investing in big data to grow their businesses. One of the biggest issues pertains to data quality. Even the most sophisticated big data tools can’t make up for this problem. Data cleansing and its purpose. Tips for successful data cleansing.

Business Analytics 109

Business Analytics Analytics Data Quality Big Data 109

O'Reilly on Data

JULY 28, 2020

This isn’t always simple, since it doesn’t just take into account technical risk; it also has to account for social risk and reputational damage. A product needs to balance the investment of resources against the risks of moving forward without a full understanding of the data landscape. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

bridgei2i

MARCH 11, 2021

From eliminating the need for human assistance in repetitive tasks to reducing the risk of human errors in manual processes – AI can do a lot for large-scale businesses. Easily understandable, highly curated, and reliable data helps Machine Learning (ML) tools evolve. What is a Data Governance Strategy? in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. The What: Data Governance Defined. Where is it?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Alation

FEBRUARY 13, 2020

Benefits of a Data Catalog. What Does a Data Catalog Do? A modern data catalog includes many features and functions that all depend on the core capability of cataloging data—collecting the metadata that identifies and describes the inventory of shareable data. Benefits of a Data Catalog. Conclusion.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. their customer insights, connected products, risk mitigation). Mitigate risk to Cloudera’s business – for example in the area of Cybersecurity, and to ensure compliance with regulatory and consumer privacy policies and concerns.

Data-driven 44

Data-driven Data Quality Risk Interactive 44

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

FineReport

MAY 31, 2023

Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming. 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.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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 311

Enterprise Deep Learning Data Governance Risk 311

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

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. This is aligned to the five pillars we discuss in this post.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

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

NOVEMBER 11, 2021

As IT leaders oversee migration, it’s critical they do not overlook data governance. Data governance is essential because it ensures people can access useful, high-quality data. Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance?

Data Governance 52

Data Governance Data Quality Metrics Metadata 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

Alation

MARCH 5, 2021

Data governance defines how data should be gathered and used within an organization. It address core questions, such as: How does the business define data? How accurate must the data be for use? Organizations have much to gain from learning about and implementing a data governance framework.

Data Governance 59

Data Governance Data Quality Dashboards Risk 59

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Before going all-in with data collection, cleaning, and analysis, it is important to consider the topics of security, privacy, and most importantly, compliance. Clean data in, clean analytics out.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

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

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 65

Data Architecture Data Lake Machine Learning Data Governance 65

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. 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. Do it faster.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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

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 fourth challenge was around using the data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

CIO Business Intelligence

JANUARY 20, 2023

But to get maximum value out of data and analytics, companies need to have a data-driven culture permeating the entire organization, one in which every business unit gets full access to the data it needs in the way it needs it. This is called data democratization. Security and compliance risks also loom.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135