Bill Schmarzo - Dell EMC

FEBRUARY 28, 2018

For example, you want to use Deep Learning to estimate how much solar energy we could generate with solar panels on the Golden Gate Bridge (that probably wouldn’t be a very popular decision in San Francisco). For example:”. Figure 5: Using RNN’s to Identify Shapes and Patterns Buried in the Telemetry Data.

Data science 110

Data science Artificial Intelligence Big data Cloud 110

Collibra

JULY 13, 2023

We’ve heard about the benefits of big data, but we now know that for many applications, it is more fruitful to focus on making sure we have good data — data that clearly illustrates the concepts we need the AI to learn. Data is food for AI, and modern AI systems need not only calories, but also high-quality nutrition.

Government 94

Government Data science Artificial Intelligence Analytics 94

Data Matters

JUNE 27, 2022

For example, contributors suggested that it would be almost impossible for messaging services to interconnect without compromising the end-to-end encryption and that such technical challenges merit a careful case-by-case assessment.

Marketing 158

Marketing Data science Privacy Artificial Intelligence 158

Collibra

AUGUST 23, 2023

As the data intelligence company, we’ve long anticipated broad adoption of AI, and Collibrians with data science and machine learning expertise have been working diligently on ways to apply AI/ML. Please provide 10 examples with options. What are the judging criteria for this hackathon?

Communications 98

Communications Data science Marketing Artificial Intelligence 98

Collibra

OCTOBER 25, 2023

If you want to implement AI governance, you may face several challenges, including: AI models are complex and require a cross-functional team for development and deployment that includes expertise in various areas such as data science, software engineering and compliance.

Government 103

Government IT Data science Compliance 103

Collibra

NOVEMBER 17, 2022

Sending Collibrians to learn new skills, connect with peers, and represent the organization at industry events like Grace Hopper is one example of how we approach career growth at Collibra. When I shared what I learned with Karina, she explained that this is one of the things she and the Data Office do at Collibra.

Data science 98

Data science IT 98

The Security Ledger

APRIL 16, 2021

Is scraping the same as hacking or just an example of “zealous” use of a social media platform? » Related Stories Episode 206: What Might A Federal Data Privacy Law Mean In the US? Is scraping the same as hacking or just an example of “zealous” use of a social media platform? And if it isn’t considered hacking…should it be?

IT 52

IT Data science Data Privacy Sales 52

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. billion by 2024, and recognized ABBYY as a Leader in the category. About Alteryx.

Analytics 40

Analytics Digital transformation Mining Data science 40

IBM Big Data Hub

FEBRUARY 10, 2022

By leveraging Artificial Intelligence and open source technologies like Python, FastAPI, JavaScript, and CouchDB, the TakeTwo solution can continue to evaluate the data it ingests, and better detect when bias exists within it. On a related note, the skills needed on projects like these go way beyond just data science.

Artificial Intelligence 54

Artificial Intelligence Data science IT Access 54

The Last Watchdog

NOVEMBER 30, 2021

In one recent example, researcher Jan Masters found a way to manipulate an API supporting subscription services offered by Peloton, makers of the popular cycling machine. In another high-profile example, Bill Demirkapi, a sophomore at Rochester Institute of Technology, was shopping for student loans when he stumbled across an Experian API.

IT 226

IT Security Big data Digital transformation 226

Bill Schmarzo - Dell EMC

MARCH 19, 2018

This is the same Amos Tversky who, along with Daniel Kahneman, was featured in Michael Lewis’s most recent book “ The Undoing Project: A Friendship That Changed Our Minds , an account of Tversky and Kahnemans’ extraordinary bond that incited a revolution in Big Data studies, among other things, and made much of Lewis’ own work possible.

Analytics 111

Analytics Data science Big data Risk 111

Collibra

APRIL 9, 2021

On that topic, I had the opportunity to speak on a webinar that brought together insurance data experts from Deloitte in the UK, and data and analytics leader Peter Jackson, who heads up group data sciences for Legal & General. Drivers for cloud adoption.

Insurance 59

Insurance Cloud Data science Analytics 59

IBM Big Data Hub

MAY 8, 2023

The advent of generative AI , where the AI manipulates your data to create new content, provides an additional risk to corporate data confidentiality. One example of this is facial recognition being used for the illegal tracking of people’s movement. Efficient and accurate AI requires fastidious data science.

Insurance 71

Insurance Risk Artificial Intelligence Government 71

Collibra

MAY 4, 2021

This jointly developed service brings together data engineering, data science, analytics and machine learning through an open lakehouse platform. With an open data and cloud platform, users need data governance to continue to reap the benefits of the open architecture.

Cloud 64

Cloud Analytics Data science Government 64

eSecurity Planet

DECEMBER 15, 2022

Unlike most other AI research projects, ChatGPT has captivated the interest of ordinary people who do not have PhDs in data science. In a week, the app gained more than one million users. They can type in queries and get human-like responses. The answers are often succinct. Across the media, the reviews have been mostly glowing.

Cybersecurity 135

Cybersecurity Phishing Data science Blockchain 135

IBM Big Data Hub

DECEMBER 19, 2023

Anomaly detection simply means defining “normal” patterns and metrics—based on business functions and goals—and identifying data points that fall outside of an operation’s normal behavior. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

Unstructured data 69

Unstructured data Artificial Intelligence Sales Manufacturing 69

erwin

APRIL 15, 2020

On a business level, decisions based on bad external data may have the potential to cause business failures. In business, data is the food that feeds the body or enterprise. Better data makes the body stronger and provides a foundation for the use of analytics and data science tools to reduce errors in decision-making.

Government 134

Government Data science Metadata Analytics 134

IBM Big Data Hub

NOVEMBER 3, 2023

Captivate your customers by making the right offer at the right time, reinforce their positive behavior, or even make better decisions in your supply chain — just to name a few examples of the extensive functionality you get when you use Apache Flink alongside Apache Kafka.

Digital transformation 78

Digital transformation Data science Big data Analytics 78

Collibra

NOVEMBER 23, 2022

The Collibra Data Office is in charge of data intelligence and governance across Collibra so we were the perfect test case for the Data Intelligence Assessment. The Collibra Data Office consists of three main verticles focusing on Data Engineering, Data Science, and Data Intelligence.

Analytics 105

Analytics Data science Government Marketing 105

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). For example, many use it to contact users who leave products in their cart or exit their website. Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection.

Marketing 51

Marketing Data science e-Discovery Artificial Intelligence 51

The Last Watchdog

JUNE 4, 2019

Two notable examples are Sourcefire, acquired by Cisco for $2.7B It’s a cybersecurity and data science “foundry” that uniquely helps create, finance and intensely coach brand-new startups manned by former cybersecurity and data science veterans of select federal research centers and national laboratories.

Cybersecurity 144

Cybersecurity Computer and Electronics Data science Marketing 144

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.

Mining 62

Mining Data science Risk IT 62

CILIP

JULY 29, 2020

Readers will be provided with an Open Heritage Data Model and an overview of the laws most relevant to open heritage data. In addition, the use and reuse of open heritage data, and how institutions publish it, are explored. family historians, amateur archaeologists, community historians).

Data science 52

Data science Libraries Archiving Communications 52

IBM Big Data Hub

SEPTEMBER 7, 2022

Do your data governance systems desperately need an overhaul or is your data visualization in need of a spruce up? Do you accept that data science takes a slight back seat while you improve the data quality?

Data science 52

Data science Customer Experience Communications Marketing 52

IBM Big Data Hub

OCTOBER 3, 2022

In addition, they needed demographic data to ensure appropriate care for the community in need. For example, if a non-Spanish-speaking advocate reaches out to a primarily Spanish-speaking community, the odds of success will be much lower. Organizations need to be able to trust their data science outcomes.

Risk 52

Risk Data science Insurance Cloud 52

Reltio

MAY 12, 2020

Joanna Walker, Global MDM Architect at AstraZeneca is a great example of a data innovator who loves to solve problems and can connect data capabilities to better business outcomes. While at the same time, they know they need to have the flexibility to meet specific functional requirements for data. Be a change agent.

Customer Experience 98

Customer Experience MDM Compliance Insurance 98

Bill Schmarzo - Dell EMC

JANUARY 31, 2018

Whether we know it or not, we have all become “Citizens of Data Science,” and the world will never be the same. Apple Core ML in the iPhone is an example of how industry leaders are seamlessly embedding powerful machine learning, deep learning, and artificial intelligence frameworks into their development and operating platforms.

Artificial Intelligence 104

Artificial Intelligence Computer and Electronics Data science Customer Experience 104

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Steps for developing an effective data strategy include: 1.

Metadata 52

Metadata Analytics Big data Unstructured data 52

Bill Schmarzo - Dell EMC

MARCH 19, 2018

This is the same Amos Tversky who, along with Daniel Kahneman, was featured in Michael Lewis’s most recent book “ The Undoing Project: A Friendship That Changed Our Minds , an account of Tversky and Kahnemans’ extraordinary bond that incited a revolution in Big Data studies, among other things, and made much of Lewis’ own work possible.

Analytics 40

Analytics Data science Big data Risk 40

Reltio

OCTOBER 22, 2020

For example, while email addresses are helpful for marketing teams who communicate largely through this channel, email addresses are not the de facto starting point for human connection, which salespeople, relationship managers, store associates, call center reps, loyalty teams or delivery teams care about. . 3) RELATIONSHIPS MATTER.

Personal data 59

Personal data Marketing Customer Experience Retail 59

IBM Big Data Hub

OCTOBER 16, 2023

GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. An AI governance toolkit lets you direct, manage and monitor AI activities without the expense of switching your data science platform, even for models developed using third-party tools.

Government 75

Government Risk Artificial Intelligence Metadata 75

IBM Big Data Hub

FEBRUARY 13, 2024

For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making. Key considerations: Tech stack: Ensure your existing technology infrastructure can handle the demands of AI models and data processing.

Artificial Intelligence 122

Artificial Intelligence Marketing Sales Communications 122

Collibra

AUGUST 14, 2023

You’ll want to assess whether it’s high-quality data or not. And you want to understand if the use of the data is legally permissible and within your organization’s policies. Usually, this step involves reaching out to relevant data owners. Maybe it’s your data science colleague who has a store of transactional data.

Government 52

Government Risk Financial Services Compliance 52

Reltio

JULY 2, 2019

Martin Squires is a leader with extensive experience in customer insight, marketing analytics & data science. Selected for the last 5 years as a member of the Data IQ Data 100 , Martin has considerable experience helping organisations drive value from building a deeper understanding of their customers.

Analytics 58

Analytics Insurance Artificial Intelligence Data science 58

CILIP

SEPTEMBER 13, 2018

Technologists are developing big data applications that are coming more into the public eye, and Industrial Revolution 4.0 In one positive example of reaction to the opportunities, LibrariesWest is sharing library and personal data between six public library services in the West Country. is gathering pace.

Artificial Intelligence 40

Artificial Intelligence Libraries Big data IoT 40

Archive-It

JULY 19, 2023

For example, a user could combine multiple institutional climate change collections thus creating the most representative research collection possible. Users will be able to browse and select for analysis public Archive-It collections, much as users can browse partner web archive collections and archived websites on archive-it.org.

Archiving 20

Archiving Access Data science Libraries 20

Archive-It

JULY 19, 2023

For example, a user could combine multiple institutional climate change collections thus creating the most representative research collection possible. Users will be able to browse and select for analysis public Archive-It collections, much as users can browse partner web archive collections and archived websites on archive-it.org.

Archiving 20

Archiving Access Data science Libraries 20