CIO Business Intelligence

MAY 15, 2024

Even if you don’t have the training data or programming chops, you can take your favorite open source model, tweak it, and release it under a new name. If you have a data center that happens to have capacity, why pay someone else?” It’s also the training data, model weights, and fine tuning. Gen AI, however, isn’t just code.

Modeling 137

Modeling Risk Software Enterprise 137

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 102

Risk Optimization Management Insurance 102

CIO Business Intelligence

APRIL 29, 2022

Launching a data-first transformation means more than simply putting new hardware, software, and services into operation. True transformation can emerge only when an organization learns how to optimally acquire and act on data and use that data to architect new processes. Key features of data-first leaders.

Digital Transformation 132

Digital Transformation Strategy Data-driven Data Strategy 132

IBM Big Data Hub

SEPTEMBER 15, 2023

For example, the regulated disclosures could be anything from estimates around Scope 3 emissions, to investor-grade data. The process will accelerate the pace at which ESG data will need to be collected, verified, and incorporated into these financially material investor disclosures.

Risk 73

Risk Reporting Data-driven Publishing 73

Alation

MARCH 14, 2023

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! The growth in the range of data job titles is a testament to the value that these experts bring to their organizations.

Statistics 97

Statistics Metrics Visualization Finance 97

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. million searches per day and 1.2

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

SEPTEMBER 7, 2023

There’s also the risk of various forms of data leakage, including intellectual property (IP) as well as personally identifiable information (PII) especially with commercial AI solutions. That said, Generative AI and LLMs appear to do all of these things, producing original, “creative” outputs by learning from input data.

Insurance 86

Insurance Risk Data-driven Finance 86

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. They don’t know exactly what data they have or even where some of it is.

Metadata 104

Metadata Management Data-driven Data Architecture 104

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

DataRobot Blog

DECEMBER 20, 2022

One might imagine that the increase in available data would lead to greater transparency and more efficient markets, but the opposite seems to be the case as increased access to massive amounts of data has made assessing real estate assets much more complex. Real Estate Data Intelligence. More is not always better.

Management 59

Management Machine Learning Optimization Modeling 59

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

NOVEMBER 23, 2021

The same could be said about data governance : ask ten experts to define the term, and you’ll get eleven definitions and perhaps twelve frameworks. However it’s defined, data governance is among the hottest topics in data management. This is the final post in a four-part series discussing data culture.

Data Governance 52

Data Governance Data-driven Data Processing Consulting 52

Andrew White

JANUARY 11, 2021

It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. The fill report is here: Leadership Vision for 2021: Data and Analytics. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

AWS Big Data

AUGUST 14, 2023

This post is the first in a series dedicated to the art and science of practical data mesh implementation (for an overview of data mesh, read the original whitepaper The data mesh shift ). Taken together, the posts in this series lay out some possible operating models for data mesh within an organization.

Management 80

Management Risk Measurement Optimization 80

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52