Data science and Mining - Information Management Today

How the Data Science Elite helped uncover a gold mine at Experian

IBM Big Data Hub

JANUARY 7, 2019

Find out more about how the IBM Data Science Elite team helped Experian succeed at better analyzing their data at Think 2019.

Data science

Data science Mining

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data science

Data science Analytics Unstructured data Artificial Intelligence

Data science vs. machine learning: What’s the difference?

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

Data science Big data Analytics Mining

Webinars

How to Achieve High-Accuracy Results When Using LLMs

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Interview with the Head of the NSA’s Research Directorate

Schneier on Security

FEBRUARY 3, 2022

The field of data science aims to solve them. ” Making sense of vast stores of unclear, often stolen data in hundreds of languages and even more technical formats remains one of the directorate’s enduring tasks.

Big data

Big data Data science Mining Access

MLOps and the evolution of data science

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data science

Data science Artificial Intelligence Paper Compliance

Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. How does text mining work?

Mining

Mining Marketing Artificial Intelligence Customer Experience

3 new steps in the data mining process to ensure trustworthy AI

IBM Big Data Hub

AUGUST 15, 2022

To help data scientists reflect and identify possible ethical concerns the standard process for data mining should include 3 additional steps: data risk assessment, model risk assessment and production monitoring. Data risk assessment. Detecting and defining bias and unfairness isn’t easy.

Mining

Mining Data science Risk IT

Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

MARCH 5, 2018

Note: throughout this blog, when I use the term “artificial intelligence,” I mean that to include other advanced analytics such as deep learning, machine learning (supervised, unsupervised, reinforcement), data mining, predictive analytics, and statistics (see Figure 1). Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).

Artificial Intelligence

Artificial Intelligence Analytics Big data Mining

ABBYY Partners with Alteryx Extending the Alteryx Analytic Process Automation Platform with Deeper Process Intelligence

Info Source

OCTOBER 6, 2020

The Alteryx APA Platform unifies analytics, data science and data-centric process automation in one self-service platform. ABBYY brings process intelligence to both data and operational processes to automate otherwise complex hand-offs. “For billion by 2024, and recognized ABBYY as a Leader in the category.

Analytics

Analytics Digital transformation Mining Data science

How to unlock a scientific approach to change management with powerful data insights

IBM Big Data Hub

JANUARY 10, 2023

Grasping these opportunities at IBM, we’re increasingly building our specialism in process mining and data analysis tools and techniques we believe to be true ‘game changers’ when it comes to building cultures of continuous change and innovation. It can show whether perceptions are real, as well as unearthing unexpected insights.

Mining

Mining Analytics Digital transformation Data science

Three trends that will help organizations modernize their data warehouse

Information Management Resources

FEBRUARY 6, 2018

The adoption of machine learning and the need for access to data beyond just data science team is changing how many firms approach information warehousing.

Data science

Data science Access Mining

Embeddable AI saves time building powerful AI applications

IBM Big Data Hub

NOVEMBER 30, 2022

So, it’s crucial for companies that want to add specific AI capabilities to their applications or workflows to do so without expanding their technology stack, hiring more data science talent, or investing in expensive supercomputing resources. Users can then mine the data using simple keyword searches to find the information they need.

Libraries

Libraries Data science Cloud Mining

How to Take Your Business to The Next Level with Data Intelligence

erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Analytics

Analytics Blockchain Artificial Intelligence Big data

Observations about Legaltech 2020 from Attendees: eDiscovery Trends

eDiscovery Daily

FEBRUARY 9, 2020

— Lilith Bat-Leah, CEDS, Director, Data Science, Fronteo. We’ll publish the rest of the observations tomorrow (including mine)! — Mike Quartararo, President, Association of Certified E-Discovery Specialists. The outpouring of support from long timers to newcomers for EDRM just warmed my heart.”.

e-Discovery

e-Discovery Education Artificial Intelligence Data science

Don’t Follow the Money; Follow the Customer!

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

See “ Optimizing the Customer Lifecycle With Customer Insights ” for more details on leveraging big data and data analytics to optimize your customer’s lifecycle. Follow the Customer Summary.

Artificial Intelligence

Artificial Intelligence Analytics Customer Experience Big data

Exploring the AI and data capabilities of watsonx

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Analytics

Analytics Data science Cloud Metadata

Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

MARCH 5, 2018

Note: throughout this blog, when I use the term “artificial intelligence,” I mean that to include other advanced analytics such as deep learning, machine learning (supervised, unsupervised, reinforcement), data mining, predictive analytics, and statistics (see Figure 1). Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).

Artificial Intelligence

Artificial Intelligence Analytics Mining Big data

#InfoGov Links Of The Week 02-17-2017

Information is Currency

FEBRUARY 17, 2017

Risk of personal data loss. The Conflict between Data Science and Cybersecurity. Cybersecurity is in direct conflict with the basis tenants of data analysis, especially big data analysis, predictive analytics and data mining. Poor User Experience. Restrict core device functionality.

MDM

MDM Big data Information governance Analytics

A brief history of data and how it helped change the world

Collibra

NOVEMBER 18, 2021

Yes, the ancient pyramids relied not only on labor and raw materials, but on data collection and analysis. . Data collection is what we do. Today, we think of Big Data as a modern concept. Cloud storage, text mining and social network analytics are vital 21 st century tools.

IT

IT Data collection Analytics Military

Celebrating 40 years of Db2: Running the world’s mission critical workloads

IBM Big Data Hub

SEPTEMBER 11, 2023

The sheer volume and velocity of the transaction workloads, the richness of data in each transaction and the data in log files is a potential gold mine for machine learning and AI applications to exploit cognitive capabilities, creating a more intelligent and secure solution.

Analytics

Analytics Cloud IoT Paper

Technology sets the pace of change in content delivery and management

CILIP

OCTOBER 8, 2019

2019 brings together content delivery and technology, looking at how areas such as AI, machine learning and data science are coming together in the content world. s technologies have the power to be just as transformative. Content delivery pioneers.

e-Delivery

e-Delivery Libraries Data science Artificial Intelligence

How Are Computers Compromised (2020 Edition)

Adam Shostack

MAY 20, 2020

Understanding the way intrusions really happen is a long-standing interest of mine. This is quite a different set of questions compared to “how long does it take to detect,” or “how many records are stolen?” ” How the intrusion happens is about questions like: Is it phishing emails that steal creds?

Mining

Mining Government Phishing Access

Our Data Governance Is Broken. Let’s Reinvent It.

John Battelle's Searchblog

JANUARY 25, 2019

First, Data. Big data, data breaches, data mining, data science…Today, we’re all about the data. How much have you thought about that word in the past two years? Given how much it’s been in the news lately, likely quite a lot. And second… Governance.

Government

Government IT Marketing ROT

Announcing OpenText AI & Analytics Cloud Editions (CE) 20.2

OpenText Information Management

APRIL 8, 2020

Until recently, the word “disruptive” was used to describe competitors, technologies and business models that could radically change the market that a company competed in. appeared first on OpenText Blogs.

Analytics

Analytics Cloud Marketing Mining

Working to Advance Library Support for Web Archive Research

Archive-It

MAY 8, 2023

ARCH supports computational research with web archive collections at scale – e.g., text and data mining, data science, digital scholarship, machine learning, and more. Participants were then introduced to Archives Research Compute Hub (ARCH).

Archiving

Archiving Libraries Data science Mining

Working to Advance Library Support for Web Archive Research

Archive-It

MAY 8, 2023

ARCH supports computational research with web archive collections at scale – e.g., text and data mining, data science, digital scholarship, machine learning, and more. Participants were then introduced to Archives Research Compute Hub (ARCH).

Archiving

Archiving Libraries Data science Mining

How the Eagles and Patriots Can Avoid a Championship Let Down: Play the Percentages

Bill Schmarzo - Dell EMC

JANUARY 29, 2018

As a standard operating practice, football front offices should apply Machine Learning to mine the large body of football game data to identify those “known unknowns” and “unknown unknowns” relationships buried in the data. Trap: Anchoring Basis. However every situation – even ones that mirror previous games – is unique.

Analytics

Analytics Risk Data science Big data

How the Eagles and Patriots Can Avoid a Championship Let Down: Play the Percentages

Bill Schmarzo - Dell EMC

JANUARY 29, 2018

As a standard operating practice, football front offices should apply Machine Learning to mine the large body of football game data to identify those “known unknowns” and “unknown unknowns” relationships buried in the data. Trap: Anchoring Basis. However every situation – even ones that mirror previous games – is unique.

Analytics

Analytics Risk Data science Big data

Don’t Follow the Money; Follow the Customer!

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

See “ Optimizing the Customer Lifecycle With Customer Insights ” for more details on leveraging big data and data analytics to optimize your customer’s lifecycle. Follow the Customer Summary.

Analytics

Analytics Artificial Intelligence Customer Experience Big data

Part 1: OMG! Not another digital transformation article! Is it about understanding the business drivers?

ARMA International

SEPTEMBER 13, 2021

Gartner (2021) defines data management as “the practices, architectural techniques, and tools for achieving consistent access to and delivery of data across the spectrum of data subject areas and data structure types in the enterprise, to meet the data consumption requirements of all applications and business processes.”

Digital transformation

Digital transformation Blockchain IT Computer and Electronics

10 ways CDOs can turn data insights into actions

Information Management Resources

APRIL 6, 2018

Analytics skills are in short supply, but demands for data-driven results are not. Here are Forrester’s top tips on how chief data officers can drive business strategy.

Analytics

Analytics Data science Mining

How to transform from data survivor to data thriver

Information Management Resources

JANUARY 26, 2018

When it comes to digital transformation, many organizations either don’t know where to start or they’re jumping off the wrong diving board.

Digital transformation

Digital transformation IT Data science Mining

If you need somebody – not just anybody – data literacy help is here

Information Management Resources

FEBRUARY 5, 2020

The report 'Data Literacy Matters: The Writing’s On The Wall' presents Forrester’s data literacy framework which components of a comprehensive data literacy program.

Data science

Data science Mining