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 68

Data Quality Data Integration Metadata Cost-Benefit 68

CIO Business Intelligence

MARCH 4, 2024

Data fabric introduces an intelligent semantic layer that orchestrates disparate data sources, applications, and services into a unified and easily accessible framework. Enabled via a data integration hub, the data fabric architecture connects, organizes, and manages data, providing a consistent view across the data ecosystem.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

CIO Business Intelligence

JANUARY 9, 2024

[Our firm’s leaders] wanted to make sure there were guidelines in place to protect the company, its data, and its people.” To get past those points, Colisto worked to educate leaders about the capabilities and risks of AI, seeking to move the company from “no to know.” What is our appetite for risk and how do we address it?

IT 140

IT Risk Cost-Benefit Enterprise 140

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

DataKitchen

OCTOBER 2, 2023

One of the most pressing issues is the ownership of databases by multiple data teams, each with its governance protocols, leading to a volatile data environment rife with inconsistencies and errors. This lack of control is exacerbated by many people and/or automated data ingestion processes introducing changes to the data.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

AWS Big Data

FEBRUARY 29, 2024

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications.

Data Governance 94

Data Governance Unstructured Data Metadata Data Lake 94

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 includes structured, unstructured, and real-time data, ensuring that the platform can handle diverse data types effectively.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

IBM Big Data Hub

AUGUST 23, 2023

This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. It is the foundation for any AI Governance practice and is crucial in mitigating a number of enterprise risks. The problem is that these use cases require training LLMs on sensitive proprietary data.

Data Governance 57

Data Governance Enterprise Modeling Risk 57

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

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

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. Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand. Data engineers are unable to make these business judgments.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 98

Analytics Insurance Big Data Uncertainty 98

Smart Data Collective

JULY 15, 2021

It helps you locate and discover data that fit your search criteria. With data catalogs, you won’t have to waste time looking for information you think you have. What Does a Data Catalog Do? This means that they can be ideal for data cleansing and maintenance. What Does a Data Catalog Consist Of?

Metadata 125

Metadata IT Data-driven Data Quality 125

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 75

Data Quality Data Lake Data-driven Metrics 75

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 192

Machine Learning Modeling Testing Risk Management 192

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

Ontotext

MARCH 8, 2023

Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. A risk issue in one financial institution could result in a domino effect for many. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

JUNE 23, 2023

This enhanced partnership allows users to gain a deeper comprehension of their data environment , enabling them to observe the fundamental modifications and transformations within their data, ultimately empowering them with invaluable data intelligence. When: Thursday, June 29, at 11:30 p.m.

Data-driven 52

Data-driven Data Processing Data Quality Enterprise 52

FineReport

MAY 31, 2023

There are also some other key challenges that will often be encountered during the process of creating financial dashboards: Data Integration : One of the primary challenges is integrating data from various sources. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

DataKitchen

DECEMBER 9, 2022

DataOps automation typically involves the use of tools and technologies to automate the various steps of the data analytics and machine learning process, from data preparation and cleaning, to model training and deployment. By using DataOps, organizations can improve. Query> When do DataOps?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Andrew White

NOVEMBER 14, 2022

How is it that trying to be aware of all your data is the first step to working out what data (or analytic) actually needs to be governed first? Catalog are useful in a small number of data governance programs only. But the fact is that the vast majority of firms do not ‘do data integration correctly’.

Data Integration 52

Data Integration Technology Data Governance Analytics 52

Jet Global

MAY 1, 2020

In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Risk to the business.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

Octopai

JUNE 26, 2020

Data governance tools are available to help ensure availability, usability, consistency, data integrity and data security. This helps establish clear processes for effective data management throughout the enterprise. Without metadata, the organization is at risk of making decisions based on the wrong data.”.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Cloudera

AUGUST 31, 2021

Leveraged delivery accelerators as well as a Data Quality framework customized by the client. The centralized complete views of verified and data-quality validated source system data within the Data Fabric helped the client streamline both security and data integration efforts across their internal application footprint.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Smart Data Collective

SEPTEMBER 25, 2019

However, according to a 2018 North American report published by Shred-It, the majority of business leaders believe data breach risks are higher when people work remotely. Whether you work remotely all the time or just occasionally, data encryption helps you stop information from falling into the wrong hands.

Technology 84

Technology Statistics Strategy Insurance 84

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 176

Testing Data Quality Predictive Modeling Metrics 176

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

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

Enterprise 80

Enterprise Data Integration Data Quality Contextual Data 80

FineReport

APRIL 26, 2023

Talend Talend is an open-source data integration platform that provides a range of software and services suitable for big data, data integration, data management, data quality, cloud storage, and enterprise application integration.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 78

Insurance Risk Data-driven Modeling 78

erwin

FEBRUARY 19, 2021

It involves establishing policies and processes to ensure information can be integrated, accessed, shared, linked, analyzed and maintained across an organization. Is it sensitive or are there any risks associated with it? Metadata also helps your organization to: Discover data. Harvest data. Better data quality.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110