Collibra

OCTOBER 15, 2020

Your organization has invested heavily in these systems, and they continuously generate valuable operational and transactional data. This data is essential to power analytics and support critical business decisions. You also need to be fully aware of the data structures of data catalogs to ensure correct mapping.

Metadata 75

Metadata Analytics Data structuring Marketing 75

Collibra

DECEMBER 1, 2020

Data lake management: Prevent a data swamp. A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured and unstructured data. The data structure and requirements are not defined until the data is needed.

Government 59

Government Analytics Marketing Unstructured data 59

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Privacy 89

Privacy Data Privacy Artificial Intelligence Risk 89

IBM Big Data Hub

DECEMBER 16, 2022

In other words, a data catalog makes the use of data for insights generation far more efficient across the organization, while helping mitigate risks of regulatory violations. A business glossary to explain the business terms used within a data asset. She also wants to predict future sales of both shoes and jewelry.

Metadata 52

Metadata Data Privacy Access Libraries 52

erwin

SEPTEMBER 10, 2020

Yet given this era of digital transformation and fierce competition, understanding what data you have, where it came from, how it’s changed since creation or acquisition, and whether it poses any risks is paramount to optimizing its value. Data Lineage Tells an Important Origin Story.

Digital transformation 131

Digital transformation Metadata Government Compliance 131

erwin

AUGUST 15, 2022

The first and most important thing to recognize and understand is the new and radically different target environment that you are most likely designing a data model when choosing a NoSQL database, namely a data lake or data lakehouse. Analytical. Data Modeling. Flexible data structures (i.e.

Cloud 52

Cloud Unstructured data Data structuring Analytics 52

erwin

MAY 14, 2021

DBMS products based on rigid schema requirements impede our ability to fully realize business opportunities that can expand the depth and breadth of relevant data streams for conversion into actionable information.

Digital transformation 80

Digital transformation Cloud Data structuring Compliance 80

eSecurity Planet

APRIL 20, 2023

Database vulnerability assessment: This makes sure that the sensitive data stored in a database is protected by examining the database configuration, data structures, access controls, and other elements that affect the database’s performance and security.

Cloud 95

Cloud Data breaches Risk Security 95

Collibra

FEBRUARY 18, 2022

Organizations need metadata management in their data management practice because there is: . Increasing need for data governance, regulatory and compliance requirements and data enablement. Increasing importance of higher data quality and trusted analytics driving business value from data.

Metadata 93

Metadata IT Government Sales 93

AIIM

DECEMBER 19, 2019

Technical Specialists: A migration could require technical support for the movement of data and questions about implementation and data structures. In addition, business users will need to do the final quality control for their information. The source and target system administrators should be involved as well.

Metadata 104

Metadata Records Management ROT Cleanup 104

ARMA International

SEPTEMBER 22, 2021

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. For example, once a health record has met the regulatory requirements, the record can be anonymized and kept for years for such purposes as medical research and predictive analytics. Artificial Intelligence.

Digital transformation 52

Digital transformation Content services IT e-Discovery 52

ARMA International

SEPTEMBER 13, 2021

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. AI using machine learning (ML) involves processing samples of data to learn. Then using what was learnt learning to run data analytics on vast amounts of content from many sources. Data Analytics.

Digital transformation 59

Digital transformation Blockchain IT Computer and Electronics 59

IBM Big Data Hub

JUNE 23, 2023

Companies need to get a good understanding of data ( structured and unstructured ), organize it, manage it in a secure manner (while complying with industry regulations) and enable instant access to the “right” data. as required for a “Gig Economy”). .”

Insurance 61

Insurance Cloud Digital transformation Customer Experience 61

Collibra

NOVEMBER 5, 2020

Organizations need metadata management in their data management practice because there is: . Increasing need for data governance, regulatory and compliance requirements and data enablement. Increasing importance of higher data quality and trusted analytics driving business value from data.

Metadata 59

Metadata Government Privacy Sales 59

CGI

NOVEMBER 26, 2014

This new connected IoT world supported by new commercial models for data storage, integration and visualisation could see the remote control tower become a reality. Allow an airport to take absolute advantage of current global technological and communication revolutions and move from a fragmented airport and become a connected airport.

IoT 40

IoT Data structuring Communications Analytics 40

erwin

MAY 27, 2020

A data modeling solution should make it possible for business and semantic metadata to be created to augment physical data for ingestion into a data catalog, which provides a mechanism for IT and business users to make use of the metadata or data structures underpinning source systems.

Metadata 98

Metadata Government Data structuring Analytics 98

CGI

JULY 19, 2018

The federal government is entering an era where data analysis is taking on even greater importance at the same time emerging technologies such as intelligent automation (IA) are enabling better and faster analysis work. The document lays out an outline for a four-part Federal Data Strategy to be developed. But it’s not just there.

Analytics 40

Analytics Government Digital transformation Data structuring 40

Everteam

MARCH 12, 2019

“By 2022, 50% of organizations will include unstructured, semistructured and structured data within the same governance program, up from less than 10% today.” Gartner Market Guide for File Analytics. Much of the data we manage today is semi-structured, so why have separate solutions to manage each one?

Unstructured data 84

Unstructured data Metadata Information governance Data structuring 84

eSecurity Planet

AUGUST 13, 2021

Founded in 1991 in Waterloo, Ontario, OpenText offers enterprise content management, networking, automation, discovery, security, and analytics services. This includes deep inspection of hundreds of protocols in a standard three-pane packet browser that encapsulates data structures. Why Do You Need Digital Forensic Software?

e-Discovery 139

e-Discovery Computer and Electronics Marketing Compliance 139

Reltio

JULY 12, 2022

And as the volume, variety, and velocity of data increases, the quality and availability of data become even more important than ever. So improving the data quality of your data should be one of your top priorities. Changing data quality demands modern technology solutions.

Customer Experience 52

Customer Experience Communications Data structuring Analytics 52

IBM Big Data Hub

MARCH 25, 2022

Around 2011, we worked with a hot gaming company with a real-time analytics use case to understand what their users were doing in the moment to optimize the gaming experience by monitoring how users interacted with the game. Co-developing with customers in gaming, banking and ridesharing.

Analytics 75

Analytics Marketing Cloud Risk 75

Robert's Db2

DECEMBER 30, 2016

Keep in mind that because the DB2 REST API is a function of the DB2 for z/OS Distributed Data Facility (DDF), SQL statements and routines invoked via that interface are eligible for zIIP engine offload (up to 60%) just as are any other SQL statements and routines that execute under DDF tasks. And on more thing. (As

Analytics 48

Analytics Access Cloud Data structuring 48

Reltio

DECEMBER 2, 2020

High Performance, Highly Available Real-time Services and Mastering: Customer master data needs to connect every critical system from initial entry or sign up through marketing, sales, billing and fulfillment to deliver omnichannel connected customer experiences. Data governance and data steward teams. Project manager.

MDM 78

MDM Data migration Digital transformation Customer Experience 78

Collibra

MARCH 1, 2022

They still have Cobolt Mainframes, relational and star schema base data warehouses and data marts. “We also implemented Hadoop’s analytics platform for our big data needs,” said Vikram. “We can realize those benefits by modernizing our data ecosystem to a cloud native ecosystem.

Metadata 52

Metadata Cloud Government Analytics 52

Collibra

MARCH 1, 2022

They still have Cobolt Mainframes, relational and star schema base data warehouses and data marts. “We also implemented Hadoop’s analytics platform for our big data needs,” said Vikram. “We can realize those benefits by modernizing our data ecosystem to a cloud native ecosystem.

Metadata 52

Metadata Cloud Government Analytics 52

Enterprise Software Blog

OCTOBER 4, 2023

Luckily, that’s where low code and App Builder™ come into play, bringing things like unmatched time-to-value, code generation capabilities, data binding, and analytics dashboards. Take advantage of an environment for visually defining the UIs, workflows, and data models of your application. And this is a major setback.

Digital transformation 59

Digital transformation Marketing IT Data structuring 59

ForAllSecure

AUGUST 27, 2020

However, as we start dealing with more complex data structures, the standard mutations in coverage-guided fuzzers become less useful and more destructive. A common approach is to treat the input as a random byte stream that the fuzzer will populate and pull values out of the stream. Why is this? Know you’re ready for Mayhem?

Libraries 40

Libraries IT Data structuring Analytics 40

ForAllSecure

AUGUST 25, 2020

However, as we start dealing with more complex data structures, the standard mutations in coverage-guided fuzzers become less useful and more destructive. A common approach is to treat the input as a random byte stream that the fuzzer will populate and pull values out of the stream. Why is this? Know you’re ready for Mayhem?

Libraries 40

Libraries IT Data structuring Analytics 40

ForAllSecure

AUGUST 25, 2020

However, as we start dealing with more complex data structures, the standard mutations in coverage-guided fuzzers become less useful and more destructive. A common approach is to treat the input as a random byte stream that the fuzzer will populate and pull values out of the stream. Why is this? Know you’re ready for Mayhem?

Libraries 40

Libraries IT Data structuring Analytics 40

erwin

AUGUST 31, 2023

Challenges and adaptations over the years Data modeling faced several challenges as technology and methodologies advanced. As data grew more intricate, traditional modeling needed to expand the meta model to keep pace with the complexity of modern data structures.

Paper 98

Paper Government Data structuring Metadata 98