CIO Business Intelligence

APRIL 29, 2022

In this new era the role of humans in the development process also changes as they morph from being software programmers to becoming ‘data producers’ and ‘data curators’ – tasked with ensuring the quality of the input. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’

Data Governance 142

Data Governance IT Risk Data Lake 142

O'Reilly on Data

JULY 28, 2020

You must detect when the model has become stale, and retrain it as necessary. The Marketing team built the first model, but because it was from marketing, the model optimized for CTR and lead conversion. Nonetheless, building a superior feature pipeline or model architecture will always be worthwhile.

Marketing 363

Marketing Experimentation Metrics Testing 363

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 339

Management Machine Learning Experimentation Metrics 339

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage is static and often lags by weeks or months.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Cloudera

AUGUST 4, 2021

Data governance used to be considered a “nice to have” function within an enterprise, but it didn’t receive serious attention until the sheer volume of business and personal data started taking off with the introduction of smartphones in the mid-2000s. Security: It must serve data throughout a system.

Data Governance 86

Data Governance Metadata Data-driven Enterprise 86

CIO Business Intelligence

MARCH 29, 2022

Fortunately, learning-based projects typically use data collected for other purposes. . It’s also important to go back to raw data to ask new questions and train new models, particularly as the world is constantly changing. You have data but don’t use it. Why does valuable data so often go unused?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

datapine

JANUARY 31, 2022

As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”. The goals were multiple: revenue growth, customer satisfaction, and speed of service.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

DataKitchen

JUNE 24, 2021

It is sad to admit this but some of our more sophisticated models, early on took somewhere from 14 to 16 months on average, and we were like, what the heck, this takes way, way, way too long for us to keep up with the demands of our customer. Bergh added, “ DataOps is part of the data fabric. Education is the Biggest Challenge.

ROI 211

ROI Metrics Measurement Cost-Benefit 211

Peter James Thomas

AUGUST 29, 2018

My role encompasses being the business driver for the data platform that we are rolling out across the organisation and its success in terms of the data going onto the platform and the curation of that data in a governed state, depending on the consumer requirements.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Andrew White

JANUARY 9, 2022

Data mesh seems to mean a network of systems and hubs connected to help cope with silos. Perhaps a data mesh is what a pure architecture might design. There are many tactics to employ that might help – including data literacy; storytelling; use of our value pyramid/business value model; use of our decision intelligence model.

Analytics 64

Analytics Measurement Modeling Data-driven 64

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

erwin

MARCH 4, 2021

So companies will be forced to classify their data and to find mechanisms to share it with such platforms.”. GDPR is also proving to be the de facto model for data privacy across the United States. Virginia residents also would be able to opt out of data collection.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

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

FEBRUARY 17, 2023

For this reason, your data program will benefit from bringing data governance and data management together. Our organization is struggling with the guardrails between the data governance and management concepts. What frameworks and operating models have you seen work well? Here’s an example.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

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

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.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Constructing A Digital Transformation Strategy: Data Enablement.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98