Bill Schmarzo - Dell EMC

FEBRUARY 6, 2018

I was recently asked to conduct a 2-hour workshop for the State of California Senior Legislators on the topic of “Big Data, Artificial Intelligence and Privacy.” Figure 3: Big Data and AI Reducing Crop Loss to Diseases. There is a bounty of free and low-cost Big Data and Artificial Intelligence training available.

Big data 87

Big data Artificial Intelligence Government Privacy 87

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 240

IT Security Big data Digital transformation 240

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

Bill Schmarzo - Dell EMC

FEBRUARY 6, 2018

I was recently asked to conduct a 2-hour workshop for the State of California Senior Legislators on the topic of “ Big Data , Artificial Intelligence and Privacy.” Figure 3: Big Data and AI Reducing Crop Loss to Diseases. There is a bounty of free and low-cost Big Data and Artificial Intelligence training available.

Big data 40

Big data Artificial Intelligence Government Privacy 40

Collibra

JULY 13, 2023

. … the bottleneck for many [AI] applications is getting the right data to feed to the software. 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.

Government 72

Government Data science Artificial Intelligence Analytics 72

IBM Big Data Hub

NOVEMBER 3, 2023

However, not all of it is necessarily actionable and some get stuck in queues or big data batch processing. Additionally, Apache Flink contextualizes your data by detecting patterns, enabling you to understand how things happen alongside each other.

Digital transformation 78

Digital transformation Data science Big data Analytics 78

Bill Schmarzo - Dell EMC

APRIL 4, 2018

Figure 1: “Driving Business Strategies with Data Science: Big Data MBA” Because in our evolving world, successful digital transformation will be the difference whether a business survives or wilts in the modern economy. Let’s walk through an example.

Digital transformation 98

Digital transformation Big data Marketing Artificial Intelligence 98

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? For example, instead of asking: “What was customer attrition last month?” Figure 7: Brainstorming Data that Might be Better Predictors of Performance.

Artificial Intelligence 111

Artificial Intelligence Analytics Big data Mining 111

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

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

Reltio

FEBRUARY 3, 2021

Reltio Connected Data Platform uniquely features big data architecture to manage massive data volumes in real-time for operational, analytical and data science use cases, and an API-first SaaS business model for rapid innovation and responsive data management. . Unparalleled Performance.

MDM 98

MDM Cloud Marketing B2C 98

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

Reltio

NOVEMBER 9, 2020

This strategy requires a tight interlock between the data strategy and technology and customer experience processes. . You can't deliver omnichannel connected customer experiences if your data is disconnected across functional silos. Rob Fuller, Customer Data Orchestration Practice Lead, Accenture Interactive.

Customer Experience 72

Customer Experience MDM Retail Data science 72

Reltio

MAY 13, 2020

Graph technology can quickly identify an HCP’s channel choice, content preferences, influence in a disease area, prescribed products and clinical trial participation, for example. For example, it can help identify an HCP engaging with different channels, or working at various locations as one, rather than multiple, people.

Analytics 59

Analytics Big data Compliance Data science 59

erwin

JUNE 11, 2020

How Business Benefits from Data Intelligence. Traditional business models and processes can be detrimental to today’s evolving data-driven society. Businesses are then introduced to modern data science and data intelligence tools to enhance and fine-tune their products and processes. Expanding big data.

Analytics 103

Analytics Blockchain Artificial Intelligence Big data 103

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

Check out “ The New Normal: Big Data Business Model Disintermediation and Disruption ” for more details on business model disruption and customer disintermediation. For example, Amazon is vertically integrating the grocery industry with their recent acquisition of Whole Foods. Customer experiences are unsatisfactory.

Artificial Intelligence 102

Artificial Intelligence Analytics Customer Experience Big data 102

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

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 73

Insurance Risk Artificial Intelligence Government 73

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 71

Unstructured data Artificial Intelligence Sales Manufacturing 71

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. Big Data: Why Should You Be Aware of It. Customer Engagement.

MDM 40

MDM Big data Information governance Analytics 40

Bill Schmarzo - Dell EMC

APRIL 4, 2018

Figure 1: “Driving Business Strategies with Data Science: Big Data MBA” Because in our evolving world, successful digital transformation will be the difference whether a business survives or wilts in the modern economy. Let’s walk through an example.

Digital transformation 40

Digital transformation Big data Marketing Artificial Intelligence 40

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

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

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

Bill Schmarzo - Dell EMC

MARCH 28, 2018

For example, digital competitors with niche products and agile delivery offerings are forcing organizations to unbundle profitable product and service offerings. One of the first concepts we learned in microeconomics was economic rent—profit earned in excess of a company’s cost of capital. the market price).

Digital transformation 106

Digital transformation Customer Experience Marketing Retail 106

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? For example, instead of asking: “What was customer attrition last month?” Figure 7: Brainstorming Data that Might be Better Predictors of Performance.

Artificial Intelligence 40

Artificial Intelligence Analytics Mining Big data 40

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

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 125

Artificial Intelligence Marketing Sales Communications 125

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

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 77

Government Risk Artificial Intelligence Metadata 77

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

Check out “ The New Normal: Big Data Business Model Disintermediation and Disruption ” for more details on business model disruption and customer disintermediation. For example, Amazon is vertically integrating the grocery industry with their recent acquisition of Whole Foods. Customer experiences are unsatisfactory.

Analytics 40

Analytics Artificial Intelligence Customer Experience Big data 40

CILIP

OCTOBER 8, 2019

Now we are in a place where Big Data and Artificial Intelligence (AI) are the ideas that are set to launch the next big thing. New conference, ConTech, which takes place in December and is in its second year aims to capitalise on the buzz about data and AI for anyone working with content ? Content delivery pioneers.

e-Delivery 40

e-Delivery Libraries Data science Artificial Intelligence 40

Bill Schmarzo - Dell EMC

FEBRUARY 20, 2018

I wanted to drill into this “1% edge” to not only verify the number, but to further understand how the “1% edge” might apply to organizations trying to effectively leverage data and analytics to power their businesses (see “ Demystifying the Big Data Business Model Maturity Index ”). Let’s walk through a fraud example.

Analytics 85

Analytics Big data Insurance Marketing 85

IBM Big Data Hub

JANUARY 10, 2023

Leveraging data to replace the ‘gut feel’ on which too many business decisions are made enables change practitioners to separate perceptions from reality and decide which processes need the most focus. For example, pin-pointing a certain user group or process which is reflecting lower levels of activity or inaccuracy of tasks.

Mining 52

Mining Analytics Digital transformation Data science 52

Bill Schmarzo - Dell EMC

MARCH 28, 2018

For example, digital competitors with niche products and agile delivery offerings are forcing organizations to unbundle profitable product and service offerings. One of the first concepts we learned in microeconomics was economic rent—profit earned in excess of a company’s cost of capital. the market price).

Digital transformation 40

Digital transformation Customer Experience Marketing Retail 40

Bill Schmarzo - Dell EMC

JANUARY 29, 2018

Necessity dictated that we become very good at recognizing patterns and making quick, instinctive survival decisions based upon those patterns (see the blog “ Human Decision-Making in a Big Data World ”). For example, humans tend to avoid risk when a positive frame is presented, but seek risks when a negative frame is presented.

Analytics 40

Analytics Risk Data science Big data 40