IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Data team morale is consistent with DataKitchen’s own research. We surveyed 600 data engineers , including 100 managers, to understand how they are faring and feeling about the work that they are doing.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

AWS Big Data

JUNE 6, 2023

Data is the lifeblood of modern businesses. In today’s data-driven world, companies rely on data to make informed decisions, gain a competitive edge, and provide exceptional customer experiences. However, not all data is created equal. AWS Glue Data Quality measures and monitors the quality of your dataset.

Data Quality 66

Data Quality Data Lake Visualization Data-driven 66

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. Embedding: The retrieved data is encoded into embeddings that the LLM can interpret.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

datapine

JANUARY 24, 2021

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. That being said, it seems like we’re in the midst of a data analysis crisis.

IT 317

IT Statistics KPI Data-driven 317

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Remember that dark data is the data you have but don’t understand. So how do you find your dark data? Analyze your metadata.

IT 133

IT Metadata Data-driven Data Governance 133

DataKitchen

MARCH 12, 2024

Key Success Metrics, Benefits, and Results for Data Observability Using DataKitchen Software Lowering Serious Production Errors Key Benefit Errors in production can come from many sources – poor data, problems in the production process, being late, or infrastructure problems. Director, Data Analytics Team “We had some data issues.

Metrics 120

Metrics Software Cost-Benefit Testing 120

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

CIO Business Intelligence

APRIL 29, 2022

This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle.

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

MAY 7, 2024

Chief data officers have a lot to think about these days. Chief among them, they must ensure responsible, compliant use of their organizations’ data in the face of increasingly complex regulatory environments across the globe. At the end of the day, it’s all the company’s data or the consumer’s data,” he adds.

Data Strategy 119

Data Strategy Data-driven Data Quality Strategy 119

Anmut

JULY 20, 2021

Does your organisation have a data driven culture? The amount of data has exploded in the last decade. Ever more organisations have started their journey to becoming data-driven and utilising data to make better decisions more often. Today, every organisation is a data company. What does this mean?

Data-driven 52

Data-driven Measurement Data Quality Software 52

Smarten

DECEMBER 11, 2019

Data Quality vs. Data Agility – A Balanced Approach! When it comes to analytical quality versus analytical agility, we might see the issue in the same light. Sometimes we are so focused on perfection that we do not see the benefit of agility. Consider the emergence of the brainstorming concept as an example.

Data Quality 52

Data Quality Predictive Modeling Data-driven Visualization 52

Octopai

OCTOBER 26, 2022

Data-driven organizations are a bad idea. Using data to drive your organization is wonderful. But data, at best, can only be a powerful vehicle, or a reliable GPS system. Except sometimes we call organizations “data-driven” when really the data is driving them up the wall. And it should be.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Anmut

MARCH 22, 2023

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models?

Measurement 52

Measurement Modeling Data Quality Data Governance 52

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

DataKitchen

OCTOBER 20, 2023

In today’s data-driven landscape, Data and Analytics Teams i ncreasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability. Data Observability platforms often need to deliver this level of customization.

Insurance 176

Insurance Metadata Data-driven Data Quality 176

CIO Business Intelligence

APRIL 24, 2024

The data platform and digital twin AMA is among many organizations building momentum in their digitization. Finally, the flow of AMA reports and activities generates a lot of data for the SAP system, and to be more effective, we’ll start managing it with data and business intelligence.” million tons of waste annually.

Digital Transformation 105

Digital Transformation Business Intelligence Unstructured Data Data Lake 105

CIO Business Intelligence

APRIL 8, 2024

Nearly 10 years ago, Bill James, a pioneer in sports analytics methodology, said if there’s one thing he wished more people understood about sabermetrics, pertaining to baseball, it’s that the data is not the point. The point is to use the data like a razor to cut through false convictions to find the truth.

Analytics 118

Analytics Broadcasting Predictive Analytics Metrics 118

Laminar Security

DECEMBER 13, 2023

In the ever-evolving digital landscape, the importance of data discovery and classification can’t be overstated. As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

Alation

MARCH 2, 2023

Instead, we got data. Lots and lots of data. It does feel, however, as if we need jet-like speed to analyze and understand our data, who is using it, how it is used, and if it is being used to drive value. This is because simply collecting data leaves it open to misinterpretation, misuse, and decay.

Metadata 52

Metadata Marketing IT Data Quality 52

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics. Is it a problem that should be solved?

Marketing 362

Marketing Experimentation Metrics Testing 362

Ontotext

FEBRUARY 12, 2024

Part one of this three-part series discussed the concept of data mesh and explored what it is and why an organization should care. Here, part two provides best practices for data mesh, including practical guidance, challenges, and limitations. Enterprises should identify and adopt specific data mesh elements to achieve velocity.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

CIO Business Intelligence

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The second-most significant barrier was the availability of quality data. Relatively few respondents are using version control for data and models. Executive Summary.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

SEPTEMBER 1, 2021

The more an enterprise wants to know about itself and its business prospects, the more data it needs to collect and analyze. Additionally, the more data it collects and stores, the better its ability to know customers, to find new ones, and to provide more of what they want to buy. Common characteristics of data-driven companies.

Data-driven 102

Data-driven Data Quality Enterprise Digital Transformation 102

Andrew White

OCTOBER 23, 2020

Almost every organization I spoke to is struggling with data and analytics and trying to work out how to re-engineer how their business leaders take decisions. Almost every organization I spoke to is struggling with data and analytics and trying to work out how to re-engineer how their business leaders take decisions. Public Sector 4.

IT 52

IT Digital Transformation Recreation/Entertainment Data Quality 52

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

IBM Big Data Hub

NOVEMBER 21, 2023

Apache Kafka is a well-known open-source event store and stream processing platform and has grown to become the de facto standard for data streaming. A schema describes the structure of data. Apache Kafka transfers data without validating the information in the messages. Kafka does not examine the metadata of your messages.

Data Quality 105

Data Quality Metadata Data-driven Optimization 105

Andrew White

OCTOBER 22, 2020

Topics : (broader/full) Data and Analytics Strategy 14. Data and Analytics Governance and/or MDM 10. Data Management 3. Data Monetization 1. Chief Data Officer/CDO 4. Chief Quality Officer 1. Director Data Mgt and Advanced Analytics 1. Data Governance 1. VP Analytics/VP Data 2.

IT 52

IT Recreation/Entertainment Data Quality Data-driven 52

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. And she is numbers driven – great! Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. What should be in that report about your data team?

Metrics 130

Metrics Data Analytics Analytics Measurement 130