CIO Business Intelligence

MAY 8, 2024

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

Data Integration 102

Data Integration IoT Cost-Benefit Machine Learning 102

BizAcuity

NOVEMBER 13, 2024

In today’s data-rich environment, the challenge isn’t just collecting data but transforming it into actionable insights that drive strategic decisions. For organizations, this means adopting a data-driven approach—one that replaces gut instinct with factual evidence and predictive insights. What is BI Consulting?

Consulting 52

Consulting Data-driven Cost-Benefit Business Intelligence 52

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 300

Testing Machine Learning Consulting Data Science 300

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

DataKitchen

JANUARY 25, 2022

Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. When internal resources fall short, companies outsource data engineering and analytics. There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. .

Consulting 244

Consulting Testing Data Lake Data Quality 244

CIO Business Intelligence

FEBRUARY 26, 2025

We actually started our AI journey using agents almost right out of the gate, says Gary Kotovets, chief data and analytics officer at Dun & Bradstreet. The problem is that, before AI agents can be integrated into a companys infrastructure, that infrastructure must be brought up to modern standards. According to the Tray.ai

IT 141

IT Enterprise Interactive Data Quality 141

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Together, these capabilities enable terminal operators to enhance efficiency and competitiveness in an industry that is increasingly data driven.

IoT 101

IoT Machine Learning Metadata Data-driven 101

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 83

Data Quality Data-driven Data Lake Metrics 83

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 279

Machine Learning Software Metadata Testing 279

CIO Business Intelligence

NOVEMBER 13, 2024

Now, picture doing that with a mountain of data. Infused with the magic of artificial intelligence (AI), DataLark revolutionizes data migration, making it faster, more efficient, and surprisingly painless. It involves shifting massive amounts of data from outdated legacy systems to a sleek, modern ERP platform.

Cost-Benefit 64

Cost-Benefit Data-driven Data Integration Data Quality 64

Alation

AUGUST 9, 2022

Today, data is more valuable to a company than it’s ever been. It can help you make data-driven decisions which can improve business performance, boost revenue, and improve efficiencies. But in the four years since it came into force, have companies reached their full potential for data integrity?

Data Integration 52

Data Integration Data Quality Measurement Data-driven 52

Wayne Yaddow

MARCH 3, 2025

These strategies can prevent delayed discovery of quality issues during data observability monitoring in production. Below is a summary of recommendations for proactively identifying and fixing flaws before they impact production data. Helps maintain business rule consistency and avoid regressions in data quality overtime.

Data Quality 52

Data Quality Strategy ROI Testing 52

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 169

Insurance Metadata Data-driven Data Quality 169

IBM Big Data Hub

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

Data Quality 63

Data Quality Data Governance People Analytics Data-driven 63

Smart Data Collective

SEPTEMBER 21, 2021

In such an era, data provides a competitive edge for businesses to stay at the forefront in their respective fields. According to Forrester’s reports, the rate of insight-driven businesses is growing at an average of 30% per year. Challenges in maintaining data. Advantages of data fabrication for data management.

Management 131

Management Internet of Things Data Quality Data Integration 131

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

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 56

Data Quality Metadata Data Governance Data-driven 56

erwin

DECEMBER 9, 2024

When it comes to using AI and machine learning across your organization, there are many good reasons to provide your data and analytics community with an intelligent data foundation. For instance, Large Language Models (LLMs) are known to ultimately perform better when data is structured. Lets give a for instance.

Metadata 52

Metadata Data Quality Sales Modeling 52

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Metrics 124

Metrics Testing Data Quality Dashboards 124

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. It describes a certain dataset’s origin, movement, characteristics and quality. Tracing the source of data is an arduous task. Data Lineage Use Case: From Tracing COVID-19’s Origins to Data-Driven Business.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

erwin

FEBRUARY 6, 2020

As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. One piece of the research that stuck with me is that 70% of respondents spend 10 or more hours per week on data-related activities.

Management 144

Management Data Governance Cost-Benefit Metadata 144

Data Virtualization

SEPTEMBER 12, 2024

Reading Time: 2 minutes In today’s data-driven landscape, the integration of raw source data into usable business objects is a pivotal step in ensuring that organizations can make informed decisions and maximize the value of their data assets. To achieve these goals, a well-structured.

Data Integration 52

Data Integration Business Objectives Data-driven Management 52

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. Data governance.

Data-driven 56

Data-driven Enterprise Data Governance Data Science 56

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. Let’s break down each step: 1.

Data Quality 105

Data Quality Data Warehouse Data-driven Reporting 105

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 Data Analytics 130

Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. You can think of a data catalog as an enhanced Access database or library card catalog system. It helps you locate and discover data that fit your search criteria.

Metadata 133

Metadata IT Data-driven Data Quality 133

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. It’s a huge productivity loss.”

Data-driven 52

Data-driven Strategy Sales Data Integration 52

IBM Big Data Hub

MARCH 25, 2022

To simplify data access and empower users to leverage trusted information, organizations need a better approach that provides better insights and business outcomes faster, without sacrificing data access controls. There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

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 117

Data Quality Unstructured Data Testing Data-driven 117

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Constructing a Digital Transformation Strategy: How Data Drives Digital.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. In fact, as companies undertake digital transformations , usually the data transformation comes first, and doing so often begins with breaking down data — and political — silos in various corners of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. Quite simply, metadata is data about data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

CIO Business Intelligence

NOVEMBER 29, 2022

By George Trujillo, Principal Data Strategist, DataStax Innovation is driven by the ease and agility of working with data. Increasing ROI for the business requires a strategic understanding of — and the ability to clearly identify — where and how organizations win with data.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

erwin

JULY 17, 2019

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. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

AWS Big Data

JULY 13, 2023

Altron is a pioneer of providing data-driven solutions for their customers by combining technical expertise with in-depth customer understanding to provide highly differentiated technology solutions. This is a guest post co-authored by Jacques Steyn, Senior Manager Professional Services at Altron Group.

Optimization 96

Optimization B2B Data Quality Sales 96