Security Affairs

JULY 3, 2023

Examples: Customer Personal Identifiable Information, transactional data, inventory records, and financial statements. Unstructured Data: Unstructured data, on the other hand, is characterized by its lack of organization and predefined format. Train employees on data security best practices.

Unstructured data 90

Unstructured data Metadata Encryption Data structuring 90

IBM Big Data Hub

DECEMBER 19, 2023

Supervised learning Supervised learning techniques use real-world input and output data to detect anomalies. These types of anomaly detection systems require a data analyst to label data points as either normal or abnormal to be used as training data.

Unstructured data 69

Unstructured data Artificial Intelligence Sales Manufacturing 69

eSecurity Planet

MAY 30, 2023

It was also trained on the company’s global threat intelligence, which included more than 65 trillion daily signals. It leverages its PaLM 2 LLM that is trained on security use cases. Let’s face it, they can be complicated to use and require extensive training and fine-tuning.

Cybersecurity 125

Cybersecurity Unstructured data Security Privacy 125

IBM Big Data Hub

FEBRUARY 14, 2024

But right now, pure AI can be programmed for many tasks that require thought and intelligence , as long as that intelligence can be gathered digitally and used to train an AI system. Generative AI can produce high-quality text, images and other content based on the data used for training.

Artificial Intelligence 85

Artificial Intelligence Retail Unstructured data Insurance 85

CILIP

JUNE 26, 2019

Stephan will make a presentation as part of breakout on breakout on data behaviour with Julian Schwarzenbach and Caroline Carruthers at the forthcoming CILIP Conference 2019 in Manchester, in which he will be focusing on the use of unstructured data in libraries. What will be the benefit from analysing unstructured data with AI?

Libraries 40

Libraries Unstructured data Artificial Intelligence Archiving 40

AIIM

JANUARY 7, 2021

Five Recommendations for Operationalizing Security for Productivity and Governance: Inventory Your Data: Know what you have, who has access to it, and where it is. A comprehensive scan of unstructured data stores can provide visibility into the highest-value data, which most often represents the biggest risks.

Unstructured data 168

Unstructured data Government Artificial Intelligence Risk 168

AIIM

OCTOBER 5, 2018

For unstructured data such as invoices, receipts, or bills of lading, to build a reliable set of rules requires analysis of potentially thousands of variants. The goal is to produce an AI, which can be trained to sort documents and data as more effectively and faster than humans. Configuration and Operational Simplicity.

Unstructured data 128

Unstructured data Marketing IT Digital transformation 128

AIIM

SEPTEMBER 2, 2021

AIIM training provides us with the following definition: Disposition is the disposal of information that has come to the end of the information lifecycle. The retention schedule must apply to all the data in an organization’s possession, not just information officially classified as “records.” What is Disposition?

IT 185

IT Unstructured data Privacy Compliance 185

eSecurity Planet

JANUARY 18, 2024

Highly sensitive files should be stored in purpose-built systems; semi-private files can be stored with strict controls and training. Data Security & Recovery Measures Reliable CSPs provide high-level security and backup services; in the event of data loss, recovery is possible.

Cloud 114

Cloud Risk Security Encryption 114

OpenText Information Management

MAY 17, 2019

One of the big challenges for organizations today is how to realize the business value currently locked in the huge amounts of unstructured data being generated. Some experts claim as much as 80 percent of data collected by organizations is unstructured – information such as emails, social media feeds and documents.

Unstructured data 45

Unstructured data Data collection Analytics 45

Everteam

JANUARY 22, 2019

The intersection of Structured and Unstructured Data. Today there is a clear separation on how you manage structured data (database, transactional data) and unstructured data (documents, text, videos, images, email, social media, etc.). Data on legal hold = <1%. Record-worthy data = <2%.

Information governance 58

Information governance Government Unstructured data Analytics 58

IBM Big Data Hub

JULY 12, 2023

Generative AI is changing the game Generative AI can be applied to an array of use cases, such as sorting and classifying written input, transforming domain-specific text into personalized summaries, identifying and extracting essential information from unstructured data, and generating code, marketing content and more.

Unstructured data 55

Unstructured data Government Compliance Marketing 55

Rocket Software

AUGUST 19, 2020

Arkivio is Rocket’s intelligent, automated data management and archiving software. It enables tiered storage, optimized backup, file system reporting, compliance, and archiving for unstructured data. It also makes it easy to implement a multi-vendor data management solution for seamless integration with NetApp.

Access 52

Access Unstructured data Archiving Compliance 52

Archives Blogs

NOVEMBER 16, 2018

Dr. Frincke argued that vast and growing sets of “noisy data” (volumes of structured and unstructured data), make AI indispensable to human analysts. The BLS receives a large amount of structured and unstructured data, particularly in the form of written descriptions submitted for injury claims.

Unstructured data 26

Unstructured data Artificial Intelligence Government Communications 26

IBM Big Data Hub

JULY 6, 2023

An online hospitality company uses data science to ensure diversity in its hiring practices, improve search capabilities and determine host preferences, among other meaningful insights. The company made its data open-source, and trains and empowers employees to take advantage of data-driven insights.

Data science 57

Data science Big data Analytics Mining 57

eSecurity Planet

SEPTEMBER 22, 2022

What is a Security Data Lake? The typical data lake serves a repository for an organization and holds unstructured data regarding company products, financial data, customer data, supplier data, and marketing information. Features to Look for in a Security Data Lake Vendor.

Security 98

Security Analytics Cloud Unstructured data 98

Info Source

NOVEMBER 8, 2018

This program provides forward-thinking partners with more stake in the game, more money in their pockets and an even better-defined path to work with Ephesoft as they help customers worldwide solve unstructured data problems through best-of-breed cloud, hybrid and on-premise solutions.”. Enabling Solution Creation.

Unstructured data 45

Unstructured data Cloud Marketing Customer Experience 45

Role Model Software

JUNE 14, 2021

Given structured data and an algorithm, they can sort through data very quickly. With a different algorithm, they can turn unstructured data into structured data very quickly. We are certainly not against “machine learning” but the reality is that computers need to be trained, too.

Artificial Intelligence 64

Artificial Intelligence Unstructured data Energy and Utilities IT 64

eSecurity Planet

DECEMBER 22, 2021

Organizations need to understand all of the data they store and collect as well as where they’re storing it. Categories for all of your organization’s data: Not every piece of information will be relevant to CCPA and require the same level of security.

GDPR 131

GDPR Compliance Data Privacy Privacy 131

Thales Cloud Protection & Licensing

OCTOBER 25, 2018

With the Vormetric Data Security Platform, agencies can establish strong safeguards around sensitive data. The Vormetric solution offers the controls required to ensure only authorized users can gain access to sensitive data at rest. It can secure unstructured data, including documents, spreadsheets, images, web pages and more.

Cybersecurity 66

Cybersecurity Education Unstructured data Risk 66

CILIP

OCTOBER 26, 2018

You need to have your structured data structured in a good place ? Then graph databases, etc, are for your unstructured data. And the challenge is to connect the structured and the unstructured in a way that makes sense to the organisation. s a recruitment process but it is also something that we try to train them in.

Artificial Intelligence 40

Artificial Intelligence Unstructured data Data structuring IT 40

Collibra

FEBRUARY 3, 2022

And bad data can rear its ugly head twice, both in the historical data used to train the predictive model and in the new data used by that model to make future decisions. Why data lakes suffer from quality issues. A data lake acts as a central repository of data.

Metadata 52

Metadata Analytics Unstructured data Government 52

CGI

AUGUST 7, 2018

Just as important, because of the actions taken to prepare for GDPR, you may now have: A data audit and registry (internal and ideally third party). Trained staff with awareness and interest. In effect, GDPR has put you in a good position to create your next generation data structures, applications and processes. IN SUMMARY.

Privacy 40

Privacy GDPR Unstructured data Marketing 40

Collibra

SEPTEMBER 9, 2022

Duplicate data increases the probability of skewed analytical results. As training data, it can also produce skewed ML models. Rule-based data quality management can help you keep a check on duplicate and overlapping records. The most common data quality problem statements. Data quality problem statement.

Analytics 110

Analytics Customer Experience Marketing Unstructured data 110

CGI

SEPTEMBER 25, 2018

Just as important, because of the actions taken to prepare for GDPR, you may now have: A registry of the data identified in an audit. Trained staff with awareness and interest. An audit regime, to maintain its accuracy. Companywide information security policies. Third-party security policies. Management awareness and interest.

Privacy 40

Privacy GDPR Cybersecurity Unstructured data 40

IBM Big Data Hub

AUGUST 28, 2023

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. Each word becomes a feature, and the frequency of occurrence represents its value.

Mining 55

Mining Marketing Artificial Intelligence Customer Experience 55

IBM Big Data Hub

AUGUST 17, 2023

This year, the USTA is using watsonx , IBM’s new AI and data platform for business. Bringing together traditional machine learning and generative AI with a family of enterprise-grade, IBM-trained foundation models, watsonx allows the USTA to deliver fan-pleasing, AI-driven features much more quickly.

Unstructured data 92

Unstructured data Metadata Government IT 92

IBM Big Data Hub

SEPTEMBER 7, 2023

The Granite family of models is no different, and so we trained them on a variety of datasets — totaling 7 TB before pre-processing, 2.4 We have developed governance procedures for incorporating data into the IBM Data Pile which are consistent with IBM AI Ethics principles.

Artificial Intelligence 104

Artificial Intelligence Unstructured data Risk Compliance 104

ChiefTech

NOVEMBER 4, 2008

1998, ‘Implementing Innovation and Technical Change', Training and Development Australia , Feb. 2003, ‘From Unstructured Data to Actionable Intelligence' [PDF], IT Pro, Nov-Dec 2003, pp.29-35. Calvert, M., Carlopio, J., Prusack, L., Borgatti, S. Liebowitz J. 7, Issue 1, pp.3-10. Porter, M. 312-318.

Unstructured data 40

Unstructured data IT 40

Collibra

JUNE 25, 2021

Duplicate data increases the probability of skewed analytical results. As training data, it can also produce skewed ML models. Rule-based data quality management can help you keep a check on duplicate and overlapping records. The most common data quality problem statements. Data quality problem statement.

Analytics 59

Analytics Customer Experience Unstructured data Metadata 59

IBM Big Data Hub

DECEMBER 1, 2023

Foundation models are pre-trained on unlabeled datasets and leverage self-supervised learning using neural network s. The supervised learning that is used to train AI requires a lot of human effort. The introduction of ChatGPT capabilities has generated a lot of interest in generative AI foundation models.

Insurance 103

Insurance Digital transformation Customer Experience Cloud 103

Everteam

APRIL 16, 2019

Machine learning makes it possible to analyze unstructured data semantically to suggest classifications based on text found. For machine learning to work, you have to provide some training sets of documents for each classification for everteam.discover to learn from. Classifying Content with everteam.discover.

ROT 40

ROT Information governance Metadata Government 40

AIIM

MARCH 13, 2018

And to boot, after years of training in studying this silver, my wife could rattle off a pretty sweet litany documenting her mother’s side of the family at the drop of a hat. “My Nancy had silver knives, forks and spoons with initials that went back to the early 1800s, for crying out loud. Ancestry.co.uk

Digital preservation 94

Digital preservation Archiving Records Management Paper 94

Info Source

JULY 12, 2018

But when it comes to unstructured data like documents, videos, and pictures, which exist en masse in enterprise environments, users can’t find things because their search tools are clunky and cumbersome.”. We have trained the system to determine whether a document is an invoice or a contract, for example,” said Reynolds. “If

ECM 40

ECM Marketing Cloud Unstructured data 40

IBM Big Data Hub

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models.

Artificial Intelligence 80

Artificial Intelligence Unstructured data Data science Customer Experience 80

IBM Big Data Hub

AUGUST 1, 2023

Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data. A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. All watsonx.ai

Artificial Intelligence 57

Artificial Intelligence Marketing Unstructured data Manufacturing 57

AIIM

JULY 23, 2020

AIIM's training groups these into the following areas: File Format Issues. Data Quality Issues. Any migration involving unstructured data, that is, individual files, is bound to run into issues migrating certain file formats. In planning and executing a migration , there are a number of issues to consider. Process Issues.

Metadata 204

Metadata Data structuring Records Management ROT 204