O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics. Is it a problem that should be solved?

Marketing 362

Marketing Experimentation Metrics Testing 362

Ontotext

NOVEMBER 2, 2023

Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”. This is partly because integrating and moving data is not the only problem.

IT 69

IT Cost-Benefit Data-driven Technology 69

CIO Business Intelligence

FEBRUARY 16, 2024

ADP remains the 500-pound gorilla in payroll and, with its rich data, can literally tell you what’s really moving the economy,” said Pete A. For most organizations, a shift to the cloud brings scalability, access to innovative tools, and the possibility of cost savings. An early partner of Amazon, the Roseburg, N.J.-based

Digital Transformation 116

Digital Transformation Experimentation Cost-Benefit Machine Learning 116

Smart Data Collective

MAY 22, 2022

Since the decisions are data-driven, you have a lower likelihood of falling victim to attacks. The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience. AI-driven protection assesses your device when a new signal is detected.

Data-driven 135

Data-driven Risk Experimentation IT 135

CIO Business Intelligence

MAY 14, 2024

In past years, reporting fatal drug overdoses has largely been a paper- and human-driven process in King County, which shares the information with state and federal agencies. In many cases, additional documents are involved in the process, such as toxicology reports.

Deep Learning 97

Deep Learning Machine Learning Reporting Experimentation 97

DataKitchen

DECEMBER 1, 2022

Data Team members, have you ever felt overwhelmed? At DataKitchen, we’re trying to give people the tools and best practices to help them succeed with data and keep their job enjoyable and rewarding. With DataOps, data teams can ship data analytics systems faster and more confidently. So don’t wait any longer.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

DataKitchen

JANUARY 20, 2021

We’ll also discuss building DataOps expertise around the data organization, in a decentralized fashion, using DataOps centers of excellence (COE) or DataOps Dojos. Test data management and other functions provided ‘as a service’ . The beauty of DataOps is that you don’t have to choose between centralization and freedom.

Metrics 243

Metrics Experimentation Measurement Testing 243

Smart Data Collective

JULY 9, 2023

E-commerce businesses around the world are focusing more heavily on data analytics. There are many ways that data analytics can help e-commerce companies succeed. Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on. billion on analytics last year.

Optimization 73

Optimization Data Analytics Analytics Data-driven 73

Insight

APRIL 28, 2020

Originally posted on Open Data Science (ODSC). In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. Designing a Data Science Interview Onsite interviews are indispensable, but they are time-consuming.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Domino Data Lab

AUGUST 6, 2021

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. With a framework and Enterprise MLOps, organizations can manage data science at scale and realize the benefits of Model Risk Management that are received by a wide range of industry verticals.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

O'Reilly on Data

APRIL 4, 2024

The race to the top is no longer driven by who has the best product or the best business model, but by who has the blessing of the venture capitalists with the deepest pockets—a blessing that will allow them to acquire the most customers the most quickly, often by providing services below cost. Friedrich A. I disagree. We will never know.

Marketing 155

Marketing Modeling Finance Experimentation 155

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

DECEMBER 6, 2023

Much of our digital agenda is around data. The migration, still in its early stages, is being designed to benefit from the learned efficiencies, proven sustainability strategies, and advances in data and analytics on the AWS platform over the past decade. Before we were quite fragmented across different technologies.

Manufacturing 97

Manufacturing Data Lake Digital Transformation Machine Learning 97

CIO Business Intelligence

FEBRUARY 7, 2024

Franchetti acknowledges that a KPI- and outcome-driven method is still appropriate for many technology rollouts, but “the organic approach is better for AI, so our deep software development subject matter experts can innovate without a targeted business outcome,” he says. “Of Today, 35% of our IT support is fully automated.

KPI 105

KPI Measurement Experimentation Finance 105

DataRobot Blog

NOVEMBER 15, 2022

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. Automate with Rapid Iteration to Get to Scale and Compliance.

Big Data 52

Big Data Experimentation Data-driven Machine Learning 52

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

NOVEMBER 15, 2022

Experiment with the “highly visible and highly hyped”: Gartner repeatedly pointed out that organisations that innovate during tough economic times “stay ahead of the pack”, with Mesaglio in particular calling for such experimentation to be public and visible. on average over the next year, somewhat lower than the projected 6.5%

Digital Transformation 143

Digital Transformation Experimentation Risk Metrics 143

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. They also have high-tech labs conducting cutting-edge research, and some have medical schools.

Recreation/Entertainment 135

Recreation/Entertainment Experimentation Modeling Data-driven 135

DataRobot Blog

MARCH 16, 2023

DataRobot was built by data scientists for data scientists, and for more than a decade we have been the only technology company solely-focused on AI and ML. We are offering customers rapid experimentation and value identification, with both code-first and no-code approaches.

Experimentation 52

Experimentation Data-driven Measurement Enterprise 52

CIO Business Intelligence

JANUARY 9, 2024

Many organizations know that commercially available, “off-the-shelf” generative AI models don’t work well in enterprise settings because of significant data access and security risks. Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks. Highlights.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Smart Data Collective

OCTOBER 13, 2021

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. Take advantage of data analytics. One of the biggest reasons AI has become so valuable is that it is so tightly integrated with data analytics. Here’s how to stay competitive as technology evolves.

Technology 120

Technology Cost-Benefit Experimentation Machine Learning 120

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Sisense

MARCH 26, 2021

Companies surveyed by Harvard Business Review Analytic Services (HBR) report that two of the most important strategic benefits of using data analytics are (1) identifying new revenue and business models and (2) becoming more innovative. 39% of companies want to identify new revenue and business opportunities with data analytics.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 77

Experimentation Modeling Deep Learning Data-driven 77

Corinium

JUNE 6, 2019

Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. The data will enable companies to provide more personalized services and product choices.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

DECEMBER 14, 2023

Reining in the rugged and remote Through rapid cycles of discovery and experimentation, Mathur and De Bernardi’s cross-functional team devised a solution that leaned heavily on additive manufacturing, more commonly known as “3D printing.” Mathur says the data-driven nature of the solution will in time strengthen the capability.

Manufacturing 100

Manufacturing Digital Transformation Experimentation Cost-Benefit 100

CIO Business Intelligence

OCTOBER 1, 2022

The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin , data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs. Data and AI as digital fundamentals.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Although TensorFlow grew by just 3%, it, too, garnered 22% share of AI/ML usage in 2019.

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. trillion on retail businesses through 2029. trillion in that year.

Unstructured Data 92

Unstructured Data Cost-Benefit Experimentation Machine Learning 92

IBM Big Data Hub

NOVEMBER 3, 2023

As a result, I see access to real-time data as a necessary foundation for building business agility and enhancing decision making. Stream processing is at the core of real-time data. Apache Kafka streams get data to where it needs to go, but these capabilities are not maximized when Apache Kafka is deployed in isolation.

Cost-Benefit 75

Cost-Benefit Experimentation Testing Digital Transformation 75

CIO Business Intelligence

DECEMBER 29, 2023

The most pressing responsibilities for CIOs in 2024 will include security, cost containment, and cultivating a data-first mindset.” Adaptability and useability of AI tools For CIOs, 2023 was the year of cautious experimentation for AI tools. Here, we detail those and others that comprise eight of the top priorities for CIOs in 2024.

Cost-Benefit 139

Cost-Benefit Digital Transformation Consulting Strategy 139

CIO Business Intelligence

JUNE 28, 2023

“These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

Smart Data Collective

JUNE 21, 2023

We also talked about some of the best AI-driven video editing applications. This frees up time for experimentation and achieving superior results. The market for AI software is booming. Precedence Research States that the market was worth $138 billion last year and it is growing exponentially.

Software 76

Software Technology Experimentation Data-driven 76

Sisense

MARCH 6, 2019

Every year there’s high anticipation to see what key message Gartner will present in the yearly Data & Analytics Summits. It’s always fun and insightful to be able to talk to so many CDOs, CIOs, data and BI professionals within 2.5 At Sisense we’ve been preaching for BI prototyping and experimentation for quite a while now.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

DataRobot Blog

JANUARY 17, 2023

As a data scientist, one of the best things about working with DataRobot customers is the sheer variety of highly interesting questions that come up. For counterparty behavior prediction: some form of structured data which contains not only won trades but also unsuccessful requests/responses. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87