CIO Business Intelligence

SEPTEMBER 10, 2024

This AI-augmented approach ensures that no critical feature falls through the cracks and that accurate requirements documents reduce the likelihood of defects. Result: 40%-50% fewer UAT issues Streamlining workflows: GenAI analyzes post-deployment metrics to optimize SDLC workflows for faster, more reliable development.

Software 121

Software Digital Transformation Testing Advertising 121

O'Reilly on Data

NOVEMBER 19, 2024

Here’s a simple rough sketch of RAG: Start with a collection of documents about a domain. Split each document into chunks. While RAG leverages nearest neighbor metrics based on the relative similarity of texts, graphs allow for better recall of less intuitive connections. at Facebook—both from 2020.

Unstructured Data 159

Unstructured Data Structured Data Modeling Statistics 159

AWS Big Data

JULY 29, 2024

In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient. You will learn about an open-source solution that can collect important metrics from the Iceberg metadata layer. This ensures real-time metrics collection every time a transaction is committed to an Iceberg table.

Metadata 112

Metadata Snapshot Data Lake Metrics 112

CIO Business Intelligence

JANUARY 23, 2024

For example, McKinsey suggests five metrics for digital CEOs , including the financial return on digital investments, the percentage of leaders’ incentives linked to digital, and the percentage of the annual tech budget spent on bold digital initiatives. As a result, outcome-based metrics should be your guide.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

CIO Business Intelligence

MAY 2, 2023

Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality.

Digital Transformation 141

Digital Transformation IT Data-driven Metrics 141

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. What Is A Manufacturing KPI?

Manufacturing 80

Manufacturing Metrics Reporting KPI 80

O'Reilly on Data

JULY 28, 2020

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 363

Marketing Experimentation Metrics Testing 363

AWS Big Data

NOVEMBER 13, 2024

The second use case enables the creation of reports containing shop floor key metrics for different management levels. Reuse of consumer-based data saves cost in extract, transform, and load (ETL) implementation and system maintenance. The team identified two use cases. End-users receive notifications with relevant details.

Metadata 75

Metadata Data Quality Digital Transformation Data-driven 75

Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence. Conclusion.

Data Quality 131

Data Quality Machine Learning Digital Transformation Big Data 131

AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

Juice Analytics

APRIL 6, 2021

At Juice, we are working everyday to create these habits and we wanted to share how we are building a data-first mindset and where we look for inspiration. Habit 1: Define shared metrics Data fluency requires getting everyone on the same page as to what matters most. How do we track “first success” for a user?

Metrics 132

Metrics Dashboards Data-driven Data Quality 132

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

AWS Big Data

SEPTEMBER 11, 2024

The application supports custom workflows to allow demand and supply planning teams to collaborate, plan, source, and fulfill customer orders, then track fulfillment metrics via persona-based operational and management reports and dashboards. The data quality (DQ) checks are managed using DQ configurations stored in Aurora PostgreSQL tables.

Data Architecture 89

Data Architecture Optimization Data Warehouse Metadata 89

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. Gartner also recently predicted that 30% of current gen AI projects will be abandoned after proof-of-concept by 2025.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

APRIL 8, 2024

Digital Athlete draws data from players’ radio frequency identification (RFID) tags, 38 5K optical tracking cameras placed around the field capturing 60 frames per second, and other data such as weather, equipment, and play type. million video frames and documents about 100 million locations and positions of players on the field.

Analytics 118

Analytics Broadcasting Predictive Analytics Machine Learning 118

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 92

Data Warehouse KPI Optimization Cost-Benefit 92

Alation

FEBRUARY 14, 2023

From rebranding data governance in your organization to demonstrating real business impacts, there’s a lot you can do to bring everyone in your business on board. The role of monitoring, measuring, and metrics So, you’ve got the first step done; you’ve implemented data governance and everyone in your organization is on board.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. But what if you could combine that information with usage metrics?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

CIO Business Intelligence

SEPTEMBER 17, 2024

Product managers then propose digital KPIs and other metrics highlighting the business benefits delivered. One area to focus on is defining AI governance , sponsoring tools for data security, and funding data governance initiatives.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

Octopai

JUNE 9, 2024

For instance, aligning patient care data from Oracle databases with operational metrics from Power BI was daunting without clear data lineage. Different departments managed their data independently, leading to silos and inconsistencies. Accurate data lineage rebuilt trust among decision-makers.

IT 52

IT Data-driven Predictive Analytics Metadata 52

datapine

APRIL 15, 2020

Working software over comprehensive documentation. The agile BI implementation methodology starts with light documentation: you don’t have to heavily map this out. But before production, you need to develop documentation, test driven design (TDD), and implement these important steps: Actively involve key stakeholders once again.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

datapine

JANUARY 21, 2020

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Another crucial factor to consider is the possibility to utilize real-time data. Enhanced data quality. It doesn’t stop here. click to enlarge**.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

O'Reilly on Data

OCTOBER 13, 2020

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

Management 251

Management Machine Learning Metrics Modeling 251

Andrew White

JULY 5, 2023

One of the points of confusion is with catalogs – or data catalogs – or analytics catalogs or metrics stores. Here I repeat what I wrote in the original blog: Use cases for a data catalog Analytics use cases are quite different to governance use cases. The fact that there are different names is one thing.

Metrics 52

Metrics Metadata Modeling Data Quality 52

DataRobot Blog

MAY 10, 2022

The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. The first step would be to make sure that the data used at the beginning of the model development process is thoroughly vetted, so that it is appropriate for the use case at hand.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Modern data catalogs also facilitate data quality checks.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

OCTOBER 5, 2021

These divergences of focus can lead to consumers feeling bogged down by overly complicated processes or leadership teams being unable to see initiative investments reap the desired rewards of their predictive business success metrics. (1). Incomplete data. Lack of commitment.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing.

Data Warehouse 112

Data Warehouse Testing Data Quality Reporting 112

Alation

AUGUST 17, 2022

Data governance policy should be owned by the top of the organization so data governance is given appropriate attention — including defining what’s a potential risk and what is poor data quality.” It comes down to the question: What is the value of your data? Risk, however, is a different challenge.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation. The Cluster Activity page gathers useful data to monitor your cluster’s live and historical metrics.

Metrics 111

Metrics Metadata Snapshot Management 111

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 Machine Learning Data Quality 52

Ontotext

JUNE 22, 2023

All derived facts can be further put into context with structured data, which improves data quality and presents researchers with clear evidence and provenance for all insights Then, Ontotext’s Target Discovery provides deeper insights into the data stored in this highly-interlinked knowledge graph, where long sequences of relations can be mined.

Metrics 52

Metrics Statistics Visualization Metadata 52

DataRobot Blog

DECEMBER 15, 2022

If your dataset is not in time order (time consistency is required for accurate Time Series projects), DataRobot can fix those gaps using the DataRobot Data Prep tool , a no-code tool that will get your data ready for Time Series forecasting. Prepare your data for Time Series Forecasting. Generate Model Compliance Documentation.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

CIO Business Intelligence

JULY 31, 2024

As an integrated manufacturing capability, Dow is a complex puzzle, and these AI models help us incorporate historical data, market trends, and customer behaviors, all of which allow us to produce a more precise demand plan. A significant Copilot use case has been finding documents. Patents are another key area for gen AI.

Manufacturing 122

Manufacturing Cost-Benefit Digital Transformation Forecasting 122

InsightOut

MAY 20, 2022

In listening to them describe their experience – what went well and not so well – and reviewing their existing approach and documentation, I have observed a number of patterns. With these projects, there are clear technical challenges that can also lead to problems, such as data quality and accessibility.

Analytics 52

Analytics Dashboards Optimization Technology 52

IBM Big Data Hub

SEPTEMBER 11, 2023

Using data, user research and human-centered design to effectively address these considerations can help you develop a clear modernization strategy that objectively drives your priorities, backlogs and roadmaps. The pain point tracker clusters the foundational data in which value metrics are then applied.

Data-driven 85

Data-driven IT Measurement Cost-Benefit 85

erwin

MARCH 8, 2019

A number of best practices and technology solutions were used to establish the data required for managing the registration and classification of data feeds: The underlying metadata is harvested followed by an initial quality check. This, among other safeguards, ensures data quality.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65