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. Capel-Davies’ advice: Focus on communication.

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 87

Metrics Machine Learning Risk Statistics 87

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 70

Risk Management Risk Management Big Data 70

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

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

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

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. Data management’s ROI Customers often ask me how to “make the case” for data management.

Strategy 116

Strategy Management Key Performance Indicator ROI 116

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

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

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? Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

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

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

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. And you, as the product manager, are caught between them.

Management 332

Management Machine Learning Experimentation Metrics 332

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 98

Data Governance Unstructured Data Metadata Data Lake 98

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

FineReport

MAY 31, 2023

Financial Performance Dashboard The financial performance dashboard provides a comprehensive overview of key metrics related to your balance sheet, shedding light on the efficiency of your capital expenditure.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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

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.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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

CIO Business Intelligence

MARCH 24, 2023

Overcoming data challenges Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. “ESG ESG data quality is the biggest challenge. revenue growth from businesses showing a lower commitment to ESG.

Risk Management 52

Risk Management Consulting Metrics Data Quality 52

Smarten

DECEMBER 3, 2023

‘Giving your team the right tools and a simple way to manage the overwhelming flow of data is crucial to business success.’ Accessible augmented analytics, allows you to transition your business users to the Citizen Data Scientist role to make better decisions, more quickly. So, what does all this mean to your business?

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

CDW Research Hub

MAY 29, 2019

Data governance helps organizations manage their information and answer questions about business performance, allowing them to better understand data, and govern it to mitigate compliance risks and empower information stakeholders. Checklist: Building an Enterprise Data Governance Program.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 76

Data Quality Data Lake Data-driven Metrics 76

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

datapine

MARCH 27, 2019

Download right here your quick summary of the customers’ data world! Unless you take the necessary precautions, you run the risk of having to deal with multiple non-common data entries that may make your stats, facts, figures, and metrics inconsistent. Focus on relevant data for relevant results.

Management 129

Management Data-driven Dashboards Visualization 129

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 82

Data Architecture Risk Management Risk Management 82

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Jet Global

MARCH 4, 2020

A manufacturing Key Performance Indicator (KPI) or metric is a well defined and quantifiable measure that the manufacturing industry uses to gauge its performance over time. The only way to stay ahead in this fiercely competitive industry is through the implementation of manufacturing KPIs and metrics. View Guide Now.

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

Data Quality 52

Data Quality IT Data Governance Sales 52

CIO Business Intelligence

JUNE 23, 2022

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. First mile/last mile impacts.

Data Quality 98

Data Quality Key Performance Indicator Metrics KPI 98

Decision Management Solutions

NOVEMBER 13, 2018

This was the leading obstacle to high impact analytics, outscoring even poor data quality or a lack of strategic support or alignment. Following this approach, everyone can clearly see what analytic will fit in the decision, how precise it needs to be, what data is needed, how it can be deployed, measured, explained, and more.

Insurance 40

Insurance Analytics Modeling Visualization 40

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

Modeling 194

Modeling Machine Learning Testing Metrics 194

IBM Big Data Hub

SEPTEMBER 11, 2023

How to quantify the impact : Quantify, articulate and measure the expected long-term benefit of a capability to justify the investment. Through the analysis of collected data, potential opportunities for improvement are uncovered. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 90

Data-driven IT Measurement Cost-Benefit 90

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

datapine

DECEMBER 17, 2019

The purpose is not to track every statistic possible, as you risk being drowned in data and losing focus. Inclusivity: Expanding on decision-making, as these kinds of dashboards and reports serve up digestible data visualizations, members of your IT department will be able to use these reporting tools with ease, even under pressure.

Reporting 173

Reporting IT Key Performance Indicator Dashboards 173

CIO Business Intelligence

AUGUST 5, 2022

If CIOs can’t master operational excellence – “keeping the lights on” – they lose credibility with their peers and run the risk that the spotty Wi-Fi in the executive conference room will overshadow new innovations. For example, you may determine that 30% of your overall SQI will be driven by the Issue Resolution quality metrics.

Metrics 105

Metrics Dashboards Measurement Data-driven 105

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics 49

Metrics Statistics Data Quality Measurement 49