datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 6) Smart and faster reporting.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

bridgei2i

MARCH 11, 2021

They have access to large amounts of data. But, the data comes from distinct sources and systems. For instance, a small business owner who does all accounting work on Excel and uses another system to send reports will have two distinct data sources to focus on. in the system. All diagnostics, alerts, etc.,

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

O'Reilly on Data

JULY 28, 2020

Many companies face a problem that’s even worse: no one knows which levers contribute to the metrics that impact business outcomes, or which metrics are important to the company (such as those reported to Wall Street by publicly-traded companies). Data Quality and Standardization. If the product isn’t “viable” (i.e.,

Marketing 363

Marketing Experimentation Metrics Testing 363

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data. The foundation for ESG reporting, of course, is data.

Reporting 100

Reporting Data Quality Strategy Data-driven 100

Alation

JANUARY 26, 2023

It’s equally important that they know the reporting structure. Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets?

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

CIO Business Intelligence

MARCH 29, 2022

A common data habit that results in missed opportunity is assuming data has no further value once it’s been used for the particular purpose. Data is ingested, processed, transformed (perhaps for a specific report or to be stored in a traditional database), and then the raw or partially processed data is discarded.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Peter James Thomas

AUGUST 29, 2018

My role today boils down to 4 key objectives – data availability, data transparency, data quality and data control. I know that ING consists of many operating areas and has adopted a federated structure with respect to data matters. This is where the process efficiency impacts good data collection.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. For example I would argue that most organizations that report their carbon footrest are not doing it consistently and nor are they doing it correctly. We have a lot of data literacy material published and we annually update our must-have roles work.

Analytics 64

Analytics Measurement Modeling Data-driven 64

erwin

MARCH 4, 2021

And when you talk about that question at a high level, he says, you get a very “simple answer,”– which is ‘the only thing we want to have is the right data with the right quality to the right person at the right time at the right cost.’. The Why: Data Governance Drivers. Why should companies care about data governance?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Domino Data Lab

JULY 22, 2019

If you look into the middle bucket, they have three things that they report in common. One is data quality, cleaning up data, the lack of labelled data. Now, working down to the mature part of this, they report two things in common. What do they report in common? You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Alation

DECEMBER 15, 2021

Modern business is built on a foundation of trusted data. 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 52

Data Governance Strategy Metadata Data Strategy 52

Alation

NOVEMBER 11, 2021

Let’s take a look at some of the key principles for governing your data in the cloud: What is Cloud Data Governance? Cloud data governance is a set of policies, rules, and processes that streamline data collection, storage, and use within the cloud. This framework maintains compliance and democratizes data.

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

Alation

FEBRUARY 17, 2023

The data governance team should define the policies, needed controls & reports and work with the technical staff (who are more data management-centric) to build these out. This is how you can better align data governance and data management by having a ‘one-team’ mindset as you work together, with a shared focus on results.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Alation

JULY 6, 2021

But first, they need to understand the top challenges to data governance, unique to their organization. Source: Gartner : Adaptive Data and Analytics Governance to Achieve Digital Business Success. As data collection and volume surges, so too does the need for data strategy. Why Do Data Silos Happen?

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Again, metadata is key.

Metadata 64

Metadata Data Governance Dashboards Software 64

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59