IBM Big Data Hub

APRIL 16, 2024

Also, Db2 seamlessly integrates with watsonx Assistant’s natural language processing capabilities to analyze unstructured data and derive insights. Watsonx Assistant retrieves information from Db2 databases to answer user queries and performs actions based on user requests.

Security 89

Security Unstructured data Retail Analytics 89

IBM Big Data Hub

MAY 19, 2023

In addition, to address the data loss issue, PT Aegis suggested replication and backups to IBM Cloud Object Storage , a highly scalable and secure cloud storage service that provides a flexible and cost-effective way to store and manage large amounts of unstructured data.

Cloud 82

Cloud Unstructured data Customer Experience Manufacturing 82

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Data science 60

Data science Big data Analytics Mining 60

CGI

DECEMBER 12, 2012

The Campaign for Real Analytics. The surge of interest in “big data” has swung our telescopes towards analytics … but we’ve yet to adjust the focus to see what really matters. Big or little, either way is fine. By chance, the CIO has just appointed a “Big Data” supremo. ravi.kumarv@cgi.com.

Analytics 40

Analytics Big data Unstructured data Retail 40

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Cloud 57

Cloud Analytics Unstructured data Compliance 57

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Metadata 52

Metadata Analytics Big data Unstructured data 52

IBM Big Data Hub

MAY 14, 2024

A generative AI agent or assistant can ingest and summarize structured and unstructured data from internal and external sources, parse through it and generate insights and patterns for financial information that can drive business value and potentially identify untapped revenue streams.

Unstructured data 76

Unstructured data Government Cloud Analytics 76

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies.

Artificial Intelligence 89

Artificial Intelligence Retail Unstructured data Insurance 89

IBM Big Data Hub

OCTOBER 12, 2022

To identify and distill the insights locked inside this sea of “unstructured” data, ESPN collaborated with IBM to teach Watson the language of football. But for decades, this treasure trove of expertise went largely untapped by fantasy footballers, who could only consume a tiny fraction of this highly valuable content. Not anymore.

Unstructured data 88

Unstructured data Cloud Risk IT 88

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Analytical. Business Focus.

Cloud 52

Cloud Unstructured data Data structuring Analytics 52

erwin

JANUARY 17, 2020

Organizations that adopt the Any 2 approach can expect greater consistency, clarity and artifact reuse across large-scale data integration, master data management, metadata management, Big Data and business intelligence/analytics initiatives. The Advantages of NoSQL Data Modeling. SQL or NoSQL?

Metadata 138

Metadata Digital transformation Unstructured data Artificial Intelligence 138

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. Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information.

Metadata 52

Metadata Data Privacy Access Libraries 52

eSecurity Planet

AUGUST 4, 2022

Opaque Systems enables machine-learning and analytics on end-to-end encrypted data in the cloud. The benefit to organizations is that they can share confidential data with each other while also ensuring compliance with data privacy regulations. Protects both structured and unstructured data. Opaque Systems.

Encryption 115

Encryption Computer and Electronics Cloud Passwords 115

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

OCTOBER 3, 2023

Managers can also use the AI models to analyze structured and unstructured data to compare players, estimate the potential upside and downside of starting a particular player and assess the impact of an injury. Once the managers have these insights, they can move ahead with the trade, cancel it or edit the trade package.

Unstructured data 97

Unstructured data Cloud Risk Artificial Intelligence 97

Reltio

OCTOBER 9, 2022

Improve Your Company’s Big Data Management for Increased ROI. quintillion bytes of data is created on the internet every day. Even the data that matters to your business is usually unstructured and disorganized, with lots of duplicates and inaccuracies. What is Big Data? The Five Vs of Big Data.

Big data 52

Big data MDM Unstructured data Analytics 52

Reltio

SEPTEMBER 16, 2019

Eduard Yanchevsky is a business leader with more than 15 years of experience in consultancy and performance management processes, combining strong analytical, problem-solving and project management skills. What are your top 3 tips or resources to share for aspiring modern data masters?

Analytics 58

Analytics Unstructured data Cloud IoT 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 59

Unstructured data Government Compliance Marketing 59

IBM Big Data Hub

AUGUST 28, 2023

Named entity recognition (NER): NER extracts relevant information from unstructured data by identifying and classifying named entities (like person names, organizations, locations and dates) within the text. Popular algorithms for topic modeling include Latent Dirichlet Allocation (LDA) and non-negative matrix factorization (NMF).

Mining 59

Mining Marketing Artificial Intelligence Customer Experience 59

IBM Big Data Hub

SEPTEMBER 19, 2022

Join SingleStore and IBM on September 21, 2022 for our webinar “ Accelerating Real-Time IoT Analytics with IBM Cognos and SingleStore ”. Why real-time analytics matters for IoT systems. IoT systems access millions of devices that generate large amounts of streaming data. Considering solutions for real-time analytics on IoT data.

Analytics 52

Analytics IoT Unstructured data Manufacturing 52

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

Information Management Resources

FEBRUARY 22, 2018

Bruce Gifford is selected for the role after serving in the P&C carrier's actuarial department since 2009.

Analytics 29

Analytics Unstructured data Big data Government 29

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

Information Management Resources

APRIL 30, 2018

Managing this crucial component of data management will help carriers get better results from their analytics, AI and blockchain initiatives.

Insurance 29

Insurance Blockchain Analytics Unstructured data 29

IBM Big Data Hub

SEPTEMBER 13, 2023

Organizations can mitigate this scenario by leveraging advanced analytics, artificial intelligence (AI) and machine learning (ML) to build next-generation capabilities today. This is especially important in customer interactions. At the same time, the customer’s history with the company is likely stored in a structured system.

Digital transformation 99

Digital transformation Unstructured data Artificial Intelligence Cloud 99

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Analytics 80

Analytics Cloud Unstructured data Libraries 80

IBM Big Data Hub

JANUARY 17, 2023

However, most of their raw data remains unused and trapped in data silos, making extracting insights difficult. The rise of cloud object storage has driven the cost of storage down and new technologies have evolved to access and query the data stored in there more efficiently. Beyond the basics with data lakehouse governance.

Metadata 52

Metadata Analytics Unstructured data Government 52

Everteam

APRIL 16, 2019

Machine learning makes it possible to analyze unstructured data semantically to suggest classifications based on text found. It will help you meet regulatory requirements much quicker (and more accurately) than manual classification. But there are also situations where manual classification is necessary.

ROT 40

ROT Information governance Metadata Government 40

IBM Big Data Hub

NOVEMBER 10, 2023

The introduction of Generative AI offers to take this solution pattern a notch further, particularly with its ability to better handle unstructured data.

CMS 105

CMS Artificial Intelligence Unstructured data Insurance 105

erwin

JUNE 27, 2019

Additional challenges, such as increasing regulatory pressures – from the General Data Protection Regulation (GDPR) to the Health Insurance Privacy and Portability Act (HIPPA) – and growing stores of unstructured data also underscore the increasing importance of a data modeling tool.

Unstructured data 81

Unstructured data Metadata Analytics GDPR 81

IBM Big Data Hub

AUGUST 16, 2022

This process begins with solid and reliable data. At the US Open, this comprises a massive volume of structured and unstructured data from a wide variety of sources: Data on 128 men and 128 women players, including age, height, weight, tour ranking and recent performance.

Unstructured data 111

Unstructured data Artificial Intelligence Analytics Cloud 111

IBM Big Data Hub

SEPTEMBER 7, 2023

At IBM we know that businesses can’t afford to take such risks, so our Granite models are trained on data scrutinized by our own “HAP detector,” a language model trained by IBM to detect and root out hateful and profane content (hence “HAP”), which is benchmarked against internal as well as public models.

Artificial Intelligence 107

Artificial Intelligence Unstructured data Risk Compliance 107

IBM Big Data Hub

AUGUST 1, 2023

This architecture delivers savings from low-cost object storage and enables sharing of large volumes of data through open table formats like Apache Iceberg, built for high performance analytics and large-scale data processing. They can also quickly and accurately translate marketing collateral into multiple languages.

Artificial Intelligence 61

Artificial Intelligence Marketing Unstructured data Manufacturing 61

eSecurity Planet

SEPTEMBER 13, 2021

Key features in a top threat intelligence platform include the consolidation of threat intelligence feeds from multiple sources, automated identification and containment of new attacks, security analytics, and integration with other security tools like SIEM , next-gen firewalls (NGFW) and EDR. Crowdsourced analytics show threat prevalence.

Analytics 113

Analytics Cybersecurity Risk Cloud 113

IBM Big Data Hub

MAY 17, 2023

It promises end-to-end solutions to manage and monitor a fleet of drones, runs inspection missions to capture high-quality data, accesses inspection reports and derives actionable information through AI-driven analytics—all through a single platform.

Energy and Utilities 85

Energy and Utilities Data collection Analytics Mining 85

IBM Big Data Hub

SEPTEMBER 13, 2023

To drive personalized actions, insights and visibility, large volumes of data (ERP, WMS, RFID and visual analytics) need to be ingested, normalized and analyzed at high speeds. Internal and external stakeholders need fast and accurate information at their fingertips to plan, manage and direct supply chains.

Customer Experience 75

Customer Experience Unstructured data Blockchain Cloud 75

Reltio

OCTOBER 28, 2020

Why is master data governance important? . But consider: Multiple studies cite poor data quality as the biggest stumbling block to any big data initiative in a business. Lack of master data governance sows inefficiency into your business, costs the bottom line, and restricts your agility. Garbage in, garbage out.

Government 52

Government MDM Big data Unstructured data 52