Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 63

Recreation/Entertainment Testing Advertising Insurance 63

CIO Business Intelligence

MAY 10, 2023

focuses on driving mobility and tapping on the then-nascent Internet of Things, the subsequent phase prominently features technology such as artificial intelligence and machine learning and ways to extend their use across every aspect of the business. With this outlook, some may expect IT spending to shrink drastically.

Enterprise 52

Enterprise Digital Transformation Internet of Things B2B 52

Hurwitz & Associates

MAY 15, 2018

To meet that challenge, Cloudera is now embarking on a major transition in its strategy that requires it to hold on to its predominant position in Hadoop analytics – and to become a provider of machine learning software supporting both on premises and public clouds. Why focus on the Global 2000 accounts? Going Forward.

Machine Learning 40

Machine Learning Data Warehouse Marketing Software 40

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. Starting from the top: Focusing on the right change and making it feel right.

Management 52

Management Data-driven Data mining Business Objectives 52

Ontotext

SEPTEMBER 2, 2020

Capturing institutional knowledge that is machine-readable is vital. From the famous Roman roads to the concrete dome of the Pantheon in Rome. It was a catastrophic failure of ‘Institutional Memory’ It wasn’t until the invention of Portland cement in the 19th century that humanity remembered how to make concrete.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

Business Over Broadway

SEPTEMBER 5, 2018

million people have been directly affected by natural disasters since 2000. Using machine learning, deep learning, and visual recognition to improve critical processes. The devastating impact of natural disasters can be measured in human suffering, loss of life and economic impact. It is estimated that 2.5 Help from IBM.

Data Science 57

Data Science Statistics Advertising Deep Learning 57

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

CIO Business Intelligence

JULY 24, 2023

“Growth, profitability, productivity, and engagement are all now part of the CIO role that 20 years ago was all about internal operations,” says Herlihy, who has been an IT executive since landing his first CIO position in 2000. Much of that work started in response to the pandemic.

IT 98

IT Sales Business Objectives Marketing 98

AWS Big Data

JULY 27, 2023

He is passionate about databases, analytics, machine learning, and architecting solutions. Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. But in addition to that, we should use a PartiQL statement to handle arrays if applicable.

Data Warehouse 85

Data Warehouse Analytics Metadata Dashboards 85

Rita Sallam

SEPTEMBER 11, 2020

The United States grew the least at only 2% from 2000 to 2016. Don’t miss the Data Science and Machine Learning Bake-Off on September 15th at 1:pm EDT. It takes a fair bit of preparation, extreme commitment, and an ability to shine under pressure. In 2016, life expectancy in the United States (78.5)

Statistics 96

Statistics Machine Learning Sales Data Science 96

FineReport

APRIL 26, 2023

What is Big Data? It is an ever-expanding collection of diverse and complex data that is growing exponentially. The term “Big” does not only refer to its size, but also to its capacity to acquire, organize, and process information beyond the capabilities of traditional databases. Why do Enterprises Need Big Data Tools?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Insight

MARCH 27, 2019

To learn more about how I built this, read on! Even after many experiments, a machine learning (ML) engineer may still not discover the best option. AutoAugment was one of the most exciting publications in 2018, and the first method using reinforcement learning for this particular problem. 2018 , blog ).

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. We use an artificially constructed imbalance dataset (based on Iris) to generate synthetic observations via our SMOTE implementation, and discuss modifications that help SMOTE handle categorical attributes. Generation of artificial examples.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Cloudera

FEBRUARY 28, 2024

Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. Alternatively, you can read about these concepts in our SRM Overview.

Management 72

Management Testing Data Processing Big Data 72

Corinium

APRIL 25, 2019

What do you recommend to organisations to help them overcome these? Yes, definitely! The last 10+ years or so have seen Insurance become as data-driven as any vertical industry. Life insurance needs accurate data on consumer health, age and other metrics of risk. You want to enable generating value with data, but also do it safely.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

FEBRUARY 13, 2020

Since the year 2000, new discoveries are coming at a fast and furious pace in many technology sectors, including software, material science, neuroscience, and genetics. And celebrating the ability for Machine Learning Data Catalogs to support data culture in every enterprise. Not everyone had inclusive access.

Machine Learning 52

Machine Learning Data-driven Big Data Technology 52

Cloudera

JUNE 25, 2019

Over 2000 customers and partners joined us in this live webinar featuring a first-look at our upcoming cloud-native CDP services. Multi-function – solves the most demanding business use cases – applying real-time stream processing, data warehousing, data science and iterative machine learning across shared data at scale.

Enterprise 89

Enterprise Machine Learning Recreation/Entertainment IoT 89

AWS Big Data

FEBRUARY 21, 2024

AWS Glue is a serverless data integration service that makes it straightforward to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. The public subnets are used so the NAT Gateway can provide internet access for the private subnets. using a text editor.

Strategy 94

Strategy Management Visualization IT 94

Domino Data Lab

DECEMBER 2, 2020

Compared to centroid-based clustering like k-means, density-based clustering works by identifying “dense” clusters of points, allowing it to learn clusters of arbitrary shape and identify outliers in the data. The anomalous points pull the cluster centroid towards them, making it harder to classify them as anomalous points. neighborhoods.

Metrics 116

Metrics KDD Testing Machine Learning 116

Sisense

FEBRUARY 24, 2021

In fact, in a 2019 edition of Industrial Management & Data Systems, a research team led by Yu Nie noted that prior to the year 2000, there were only six chief data officers in the world. Whatever a company does, how it uses data is a key differentiator in its success or failure. The role is a relative newcomer to the boardroom.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

Occam's Razor

MAY 2, 2017

The very best analysts are know what matter’s the most are not the insights from big data but clear actions and compelling business impact from usually a smaller subset of key data. The very best analysts practice the above principles every day in every dimension of their jobs. It is that practice that I try to discern when I do job interviews.

Metrics 141

Metrics Key Performance Indicator B2B Measurement 141

CDW Research Hub

AUGUST 14, 2019

In this post, we’ll look at structuring happy and unhappy conversation paths, various machine learning policies and configurations to improve your dialogue model, and use a transfer learning-based language model to generate natural conversations. Rasa recently released version 1.0, Rasa recently released version 1.0,

Interactive 53

Interactive Modeling Machine Learning Testing 53

Domino Data Lab

AUGUST 29, 2019

The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. It also covers using Keras to construct a deep Q-learning network that learns within a simulated video game environment. Introduce families of deep RL agents beyond deep Q-learning. Introduction.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

The Unofficial Google Data Science Blog

APRIL 23, 2024

In geometry, two points or measurements determine a line, but in our setting, only one experiment would be needed to learn a straight-line model relating parameters and metrics, because we already know that the line goes through the origin (if we do not change system parameters, then metrics will not change either).

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

DECEMBER 12, 2018

And then I moved from Madison, Wisconsin to San Francisco in 2000, to chase the dotcom dream. Certainly interesting to hear that your background started in the dotcom age as I actually worked at a dot com back in 2000. So, that’s kind of how I got introduced to databases and SQL systems. Michael Moreno: Nice! Interesting times.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

Peter James Thomas

AUGUST 30, 2018

Limitations in the state of the art in machine learning. It is indeed true that Machine Learning can be quite good at dealing with some types or bad or missing data. The phrase came to mind for me today when coming across the following exhibit: © Business Over Broadway (2018). Limitations of tools.

Data Science 75

Data Science Data Quality Machine Learning Business Intelligence 75

Jet Global

OCTOBER 25, 2023

Every day, more companies unlock the potential of artificial intelligence (AI) and machine learning. When AI and machine learning are utilized in embedded analytics, the results are impressive. Much of this can be seen in modern solutions that offer advanced predictive analytics.

Analytics 52

Analytics Predictive Analytics Machine Learning Software 52

Jet Global

FEBRUARY 21, 2024

Predictive Analytics Predictive analytics, machine learning and artificial intelligence have lit a fire under your customers. And for three-quarters of application developers (71%), 40% or more of their customers and end users customize their own dashboards and reports. The Embedded Analytics Buyer’s Guide Download Now 2.

Analytics 52

Analytics Dashboards Predictive Analytics Software 52

Jet Global

JULY 17, 2023

Predictive analytics is a branch of analytics that uses historical data, machine learning, and Artificial Intelligence (AI) to help users act preemptively. Predictive analytics answers this question: “What is most likely to happen based on my current data, and what can I do to change that outcome?”

Predictive Analytics 52

Predictive Analytics Analytics Statistics Reporting 52

Jet Global

FEBRUARY 1, 2024

Embedded AI and machine learning models give your customers the foresight they need to make informed decisions, optimize resources, and gain a competitive edge. Get your application to market faster with built-in data power. Get to market faster, deliver true value, and stand out in the crowd.

Analytics 52

Analytics Dashboards Reporting Marketing 52

Jet Global

JULY 17, 2023

To improve the effectiveness of the data cleaning process, the current trend is to migrate from manual data cleaning to more intelligent, machine learning-based processes. In fact, most project teams spend 60 to 80 percent of total project time cleaning their data—and this goes for both BI and predictive analytics.

Predictive Analytics 52

Predictive Analytics Reporting Software Strategy 52

Jet Global

NOVEMBER 15, 2021

A Tax Key Performance Indicator (KPI) or metric is a clearly defined quantifiable measure that an organization, or business, uses to measure the success of its Tax Function over time. Since every organization has its own manner of operation, the KPIs or metrics used for tax will vary from one organization to another.

Metrics 52

Metrics Reporting KPI Risk Management 52

Jet Global

MAY 12, 2023

Users can track sales events, analyze customer behavior, and even predict future sales trends using advanced machine learning algorithms. With this information, they can identify areas for improvement, optimize the user experience, and ultimately drive greater success for the product. Product user experience data for developers.

Analytics 52

Analytics Slice and Dice Sales Cost-Benefit 52

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. This article and paired Domino project provide a brief introduction to working with natural language (sometimes called “text analytics”) in Python using spaCy and related libraries. the the DET True?

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. It is a complex and challenging task that requires careful planning, analysis, and execution. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic. It will show you what embedded analytics are and how they can help your company. It will show you how to select the right solution and what investments are required for success. that gathers data from many sources. Consider Delta.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52