CIO Business Intelligence

MAY 5, 2022

The boom in data science continues unabated. The work of gathering and analyzing data was once just for a few scientists back in the lab. Now every enterprise wants to use the power of data science to streamline their organizations and make customers happy. Data scientists use them to swap ideas and deliver ideas.

Data Science 130

Data Science Analytics Machine Learning Optimization 130

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Data scientists are in demand: the U.S. Forecast Time Series at Scale with Google BigQuery and DataRobot. Read the blog.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. As a DataRobot data scientist , I have worked with team members on a variety of projects to improve the business value of our customers.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

JUNE 7, 2022

It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics methods and techniques.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Rocket-Powered Data Science

MARCH 19, 2021

The determination of winners and losers in the data analytics space is a much more dynamic proposition than it ever has been. One CIO said it this way , “If CIOs invested in machine learning three years ago, they would have wasted their money. A lot has changed in those five years, and so has the data landscape.

Internet of Things 259

Internet of Things Analytics IoT Prescriptive Analytics 259

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. On premises or in SAP cloud. Per user, per month.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. How to prepare: No prior computer science or programming knowledge is necessary.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

NOVEMBER 14, 2022

With organizations increasingly focused on data-driven decision making, decision science (or decision intelligence) is on the rise, and decision scientists may be the key to unlocking the potential of decision science systems. Commonly used models include: Statistical models. Forecasting models.

Data mining 144

Data mining Data-driven Statistics OLAP 144

datapine

MARCH 31, 2022

According to the US Bureau of Labor Statistics, demand for qualified business intelligence analysts and managers is expected to soar to 14% by 2026, with the overall need for data professionals to climb to 28% by the same year. A background in (or a firm grasp of) data warehousing and mining.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Data Science and Beyond

DECEMBER 31, 0001

It’s mainly focused on data science. I’m an experienced data scientist and software engineer with a strong background in computer science, programming, machine learning, and statistics. This website/blog is mostly meant to group together stuff I write in various places.

Statistics 52

Statistics Forecasting Machine Learning Data Science 52

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Provide the right predictive analytics tools to transition business users into Citizen Data Scientists and achieve the kind of results this type of initiative can deliver.’.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses.

Deep Learning 85

Deep Learning Machine Learning Forecasting Visualization 85

DataRobot Blog

MAY 23, 2022

Department of Transportation Data. Example of border transport data from USDOT. Department of Transportation (USDOT) Bureau of Transportation Statistics (BTS) provide publicly-available monthly summary statistics for both the U.S.-Canada The database contains entry data from Mexico to the U.S. Canada and U.S.-Mexico

Forecasting 59

Forecasting Statistics Machine Learning Modeling 59

FineReport

MARCH 24, 2024

Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making. Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis.

Statistics 52

Statistics Data mining Visualization Reporting 52

Smart Data Collective

SEPTEMBER 16, 2020

These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data. These statistical models are growing as a result of the wide swaths of available current data as well as the advent of capable artificial intelligence and machine learning.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

Business Over Broadway

MAY 22, 2019

Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration. How employees can drive transformation and emerging technology adoption: Both are data-heavy endeavors; We know that statistics/math knowledge is related to data science project success.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Smart Data Collective

SEPTEMBER 19, 2022

Statistics show that 93% of customers will offer repeat business when they encounter a positive customer experience. However, fintech businesses can use big data and machine learning to build fraud detection systems that uncover anomalies in real time. Forecasting Future Market Trends. Fraud detection.

Big Data 129

Big Data ROI Measurement Risk 129

Smart Data Collective

OCTOBER 7, 2023

Marco Cerliani has a great article in Towards Data Science on the benefits of AI in the people tracing field. They developed a new app that uses machine learning to track signals through walls , which can help people track those using wearable tech. MIT recently had a huge breakthrough in this field.

Technology 92

Technology Snapshot Data-driven Machine Learning 92

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Strong patterns, if found, will likely generalize to make accurate predictions on future data. Machine learning provides the technical basis for data mining.

Data mining 77

Data mining KDD Data Science Forecasting 77

IBM Big Data Hub

AUGUST 7, 2023

This article, part of the IBM and Pfizer’s series on the application of AI techniques to improve clinical trial performance, focuses on enrollment and real-time forecasting. This results in many groups using a large gamut of AI-based tools that are not fully integrated into a cohesive system and platform.

Optimization 55

Optimization Forecasting Data-driven Strategy 55

Rita Sallam

APRIL 2, 2023

We explored these questions and more at our Bake-Offs and Show Floor Showdowns at our Data and Analytics Summit in Orlando with 4,000 of our closest D&A friends and family. The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms.

Optimization 52

Optimization Machine Learning Insurance Risk 52

Smart Data Collective

NOVEMBER 14, 2019

Gaming organizations have started to use big data to develop a deeper understanding of target customers. They have refined their data decision-making approaches to include new predictive analytics models to forecast trends and adapt to evolving customer behavior. Industry growth has averaged about 5% a year.

Predictive Analytics 79

Predictive Analytics Analytics Forecasting Modeling 79

Analytics Vidhya

APRIL 26, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post How to check Stationarity of Data in Python appeared first on Analytics Vidhya. Introduction Hello readers! In our routine life, we come.

Data Science 264

Data Science Publishing Analytics Forecasting 264

Sisense

APRIL 15, 2021

Augmented analytics (according to Gartner, which would know), uses technologies “such as machine learning [ML] and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and BI platforms.” Simplify analytics with AI.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

Smart Data Collective

OCTOBER 14, 2019

From artificial intelligence and machine learning to blockchains and data analytics, big data is everywhere. A global retailer like Amazon with its same-day shipping and multi-channel services might have billions of data points across several sectors. Gartner estimates a retail IT spend forecast of $210.9

Big Data 74

Big Data Software Data mining Prescriptive Analytics 74

Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Cutting straight right to the chase, Hurst exponent is a. The post Using Hurst Exponent to analyse the Stock and Crypto market with Python appeared first on Analytics Vidhya.

Marketing 234

Marketing Data Science Publishing Analytics 234

Smarten

AUGUST 21, 2019

” There are many features and benefits to the Smarten approach to Advanced Data Discovery. Here are just a few: Self-Serve Data Preparation – Self-Serve Data Preparation empowers business users with access to meaningful data and prepares data for analysis without the assistance of data scientists or ETL experts or IT staff.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

IBM Big Data Hub

FEBRUARY 13, 2024

Like diligent students, these generative models soak up information and identify patterns, structures and relationships between data points, which is how they learn the grammar of poetry, artistic brushstrokes and musical melodies. Imagine each data point as a glowing orb placed on a vast, multi-dimensional landscape.

Enterprise 118

Enterprise Modeling Testing Data-driven 118

Birst BI

AUGUST 23, 2018

A key goal of AI or machine learning automation is to have machines complete tasks for you, freeing up time so you can focus on the more complex, higher-value tasks. However, there are simply not enough data scientists in the world to deliver on the AI potential. The Outsourcing of Data Science Functions.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 74

Machine Learning Modeling Deep Learning Predictive Modeling 74

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. There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Agreeing on metrics.

Marketing 361

Marketing Experimentation Metrics Testing 361

Smarten

DECEMBER 17, 2018

Tools like Assisted Predictive Modeling allow the average business user to become a Citizen Data Scientist with tools that offer guidance and auto-suggestions to help the user arrive at the outcome they need without being frustrated or having to call in an army of analysts and IT staff to help them complete their analysis.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. Data Requirements. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. What is MMM?

Machine Learning 52

Machine Learning Sales Measurement ROI 52

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. Without uncurtailed and unlimited access to modeling tools, data science teams will be handcuffed in their work.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Rita Sallam

JULY 22, 2016

Research VP, Business Analytics and Data Science. Again, check out the Critical Capabilities for BI and Analytic Platforms for how each vendor compares. We are on the cusp of the next wave of BI market disruption beyond the current one started by Tableau and Qlik – but that’s for my next blog post. Enjoy your summer!!

Analytics 40

Analytics Business Intelligence Metadata Statistics 40