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.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

Smart Data Collective

JUNE 19, 2019

The Relationship between Big Data and Risk Management. Big data calls for complex processing, handling, and storage system, which may include elements such as human beings, computers, and the internet. Tips for Improving Risk Management When Handling Big Data. Risk Management Applications for Analyzing Big Data.

Risk Management 71

Risk Management Risk Management Big Data 71

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

APRIL 8, 2024

Working with partner Amazon Web Services (AWS), the NFL has developed Digital Athlete, a platform that uses computer vision and ML to predict which players are at the highest risk of injury based on plays and their body positions. Souza’s advice: Cultivate curiosity.

Analytics 118

Analytics Broadcasting Predictive Analytics Metrics 118

IBM Big Data Hub

NOVEMBER 29, 2023

To build that trust and drive broad adoption, vendors of synthetic data generation tools will need to address two critical questions that many business leaders ask: Will synthetic data expose my business to additional data privacy risks? How accurately does synthetic data reflect my existing data?

Metrics 88

Metrics Machine Learning Risk Statistics 88

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Any metric can and will be abused.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

JUNE 9, 2023

A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Without it, organizations incur a significant opportunity cost.

Strategy 116

Strategy Management Key Performance Indicator ROI 116

Alation

AUGUST 17, 2022

We’ve seen the emergence of new, less invasive approaches, yet the question remains: What do CIOs think is most required to deliver a successful data governance program? The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. If your definitions are bad, so is your governance/risk/security.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

IBM Big Data Hub

JANUARY 15, 2024

How do organizations avoid the digital risks of ‘technology misuse’ and achieve efficient innovation that ‘technology promotes production’? While optimizing management mechanisms for cost reduction, efficiency enhancement, and risk mitigation. The path of digital transformation is fraught with challenges.

Digital Transformation 75

Digital Transformation Insurance Optimization ROI 75

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. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. The Active Data Ratio metric determines the percentage of datasets that deliver value.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Laminar Security

DECEMBER 13, 2023

Close to 70% of respondents in an ISC report indicated that they believe their organization lacks requisite cybersecurity staff to handle cloud data risk effectively. Learn in this article how Laminar harnesses AI for data discovery and classification and reduces public cloud data risks.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

Smart Data Collective

SEPTEMBER 28, 2022

One of the most important is that it helps to increase the reliability of your data. Data quality issues can arise from a variety of sources, including: Duplicate records Missing records Incorrect data. The proper use of data management solutions can help you identify these problems and correct them quickly and easily.

Big Data 108

Big Data Management Data Quality Cost-Benefit 108

CIO Business Intelligence

NOVEMBER 13, 2023

Inadequate data management and governance Data is at the heart of digital transformation, and companies that don’t have adequate data management processes in place are likely to struggle. Ensuring data quality, privacy, and security is essential.

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? (2) Why should your organization be doing it and why should your people commit to it? (3) In short, you must be willing and able to answer the seven WWWWWH questions (Who?

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Alation

AUGUST 9, 2022

But almost all industries across the world face the same challenge: they aren’t sure if their data is accurate and consistent, which means it’s not trustworthy. This can cause anything from day-to-day issues to significant business problems and risks. Many confuse data integrity with data quality.

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

Smart Data Collective

DECEMBER 21, 2022

This market is growing as more businesses discover the benefits of investing in big data to grow their businesses. One of the biggest issues pertains to data quality. Even the most sophisticated big data tools can’t make up for this problem. Data cleansing and its purpose.

Business Analytics 113

Business Analytics Analytics Data Quality Big Data 113

Alation

FEBRUARY 14, 2023

In this day and age, regardless of industry, keeping data protected and its uses understood is vital. No business wants to have the PR nightmare of a data leak or personal data being used without the correct permissions. This is where successful data governance programs can act as a savior to many organizations.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 94

Strategy Data Architecture Cost-Benefit Reporting 94

erwin

MARCH 25, 2021

And with many competing projects and activities vying for people’s time, it must be clear to people why choosing data governance activities will have a direct benefit to them. Usually we talk about benefits which are rather qualitative measures, but what we need for decision-making processes are values,” Pörschmann says. “We

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

Anmut

APRIL 6, 2023

What are the Benefits of Doing a Data Maturity Assessment? How do you do a Data Maturity Assessment? What does a Data Maturity Assessment Measure? What makes a Good Data Maturity Assessment? What is a Data Maturity Assessment? What does a Data Maturity Assessment Measure?

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

AWS Big Data

FEBRUARY 29, 2024

Implement data privacy policies. Implement data quality by data type and source. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail. Link structured and unstructured datasets.

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 3) Where will your data come from?

IT 317

IT Statistics KPI Data-driven 317

DataKitchen

NOVEMBER 18, 2022

In addition to the tracking of relationships and quality metrics, DataOps Observability journeys allow users to establish baselines?concrete concrete expectations for run schedules, run durations, data quality, and upstream and downstream dependencies. Storing Run Data for Analysis.

Testing 130

Testing Statistics Measurement Metrics 130

FineReport

APRIL 9, 2024

Moreover, BI platforms provide the means for organizations to harness their data assets effectively, leading to improved customer satisfaction through personalized services and targeted marketing initiatives. This framework ensures that data remains accurate, consistent, and secure across all levels of the organization.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

datapine

MAY 31, 2022

Like many other branches of technology, security is a pressing concern in the world of cloud-based computing, as you are unable to see the exact location where your data is stored or being processed. This increases the risks that can arise during the implementation or management process. Cost management and containment. Compliance.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

erwin

JANUARY 11, 2019

It’s only when companies take their first stab at manually cataloging and documenting operational systems, processes and the associated data, both at rest and in motion, that they realize how time-consuming the entire data prepping and mapping effort is, and why that work is sure to be compounded by human error and data quality issues.

Data Governance 40

Data Governance Risk Metadata Management 40

CIO Business Intelligence

JUNE 30, 2023

All of this renewed attention on data and AI, however, brings greater potential risks for those companies that have less advanced data strategies. As these trends continue to evolve, building your data strategy around the principles of openness and governance assures trust in the data.

Internet of Things 104

Internet of Things Strategy Data Strategy Risk 104

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Monitoring is another pillar of Data Journeys, extending down the stack. Moreover, cost monitoring ensures that your data operations stay within budget and that resources are used efficiently.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Ontotext

JULY 6, 2023

Let’s consider an example about risk and opportunity event detection. Case studies The risk and opportunity event detection use case discussed above combines all of Ontotext’s capabilities: storing and managing large amounts of data adding meaning to it (e.g.,, The solution brings many business benefits.

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

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. Data quality Data quality is essentially the measure of data integrity.

Data Quality 68

Data Quality Data Integration Metadata Cost-Benefit 68

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. As such, you’re able to gain all the insights you need while avoiding having to overhaul your environment.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Octopai

JUNE 19, 2023

Data Catalogs also allow for Improved Collaboration by serving as a central repository for enterprise data, a data catalog facilitates collaboration among different teams. Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. That’s where model debugging comes in. Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

O'Reilly on Data

OCTOBER 22, 2020

It’s also a good indirect measure of training data quality: a team that does not know where their data originated is likely to not know other important details about the data as well. ML models directly involved in critical safety systems are generally easy to identify as areas of concern.

Consulting 296

Consulting Risk Cost-Benefit Modeling 296