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

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use. Infrastructure.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

FineReport

MAY 31, 2023

Financial indicators, such as revenue, gross profit, asset to debt ratio, current ratio, turnover, and price-earnings (P/E) ratio, serve as key measures of profitability, solvency, operational capability, and market valuation. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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 86

Data Governance Metadata Data-driven Enterprise 86

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. Identify and influence big bets in the market. Our journey to becoming even more data-driven is exactly the same as what our customers are going through. their customer insights, connected products, risk mitigation).

Data-driven 44

Data-driven Data Quality Risk Interactive 44

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 318

Enterprise Deep Learning Data Governance Risk 318

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

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. For example, you can use C360 to segment and create marketing campaigns that are more likely to resonate with specific groups of customers. faster time to market, and 19.1%

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

erwin

FEBRUARY 28, 2019

When you think of real-time, data-driven experiences and modern applications to accomplish tasks faster and easier, your local town or city government probably doesn’t come to mind. But municipal government is starting to embrace digital transformation and therefore data governance.

Digital Transformation 106

Digital Transformation Data Governance Data-driven Data Warehouse 106

CDW Research Hub

NOVEMBER 29, 2021

Data collection: IoT infrastructure often serves as the nucleus to integrate data from multiple sensors— and this data must be modeled processed to achieve your desired outcome. Data modeling: Modeling is necessary to normalize this data across all platforms and sensor groups. Layer 6: Applications.

IoT 89

IoT Cost-Benefit Internet of Things ROI 89

Andrew White

JANUARY 9, 2022

What is a Market? . How important is the role of the citizen data scientist, and what recommendations do you have for organizations looking to augment their data science teams by developing analysts and domain experts into this role? For example, you don’t and can’t hire a citizen data scientist or any citizen role.

Analytics 64

Analytics Measurement Modeling Data-driven 64

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

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. For this purpose, you can think about a data governance strategy. It’s that simple.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

OCTOBER 19, 2021

This can make collaboration across departments difficult, leading to inconsistent data quality , a lack of communication and visibility, and higher costs over time (among other issues). In some cases, the teams may not have even realized that they were both collecting the same data from customers! What Causes Data Silos?

Recreation/Entertainment 52

Recreation/Entertainment Sales Data-driven Marketing 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 59

Data Architecture Data Lake Machine Learning Data Governance 59

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

CIO Business Intelligence

JANUARY 20, 2023

In particular, companies that were leaders at using data and analytics had three times higher improvement in revenues, were nearly three times more likely to report shorter times to market for new products and services, and were over twice as likely to report improvement in customer satisfaction, profits, and operational efficiency.

Data Lake 125

Data Lake Data-driven Finance Data Architecture 125

Alation

OCTOBER 12, 2021

What new market opportunities exist? Enterprise data analytics enables businesses to answer questions like these. Having a data analytics strategy is a key to delivering answers to these questions and enabling data to drive the success of your business. Implementing adaptive, active data governance.

Strategy 52

Strategy Enterprise Analytics Data Governance 52