DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning.

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Forecasting Modeling ROI Machine Learning 81

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. These data science teams are seeing tremendous results—millions of dollars saved, new customers acquired, and new innovations that create a competitive advantage.

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Experimentation Forecasting Data-driven Machine Learning 145

CIO Business Intelligence

JANUARY 21, 2025

times compared to 2023 but forecasts lower increases over the next two to five years. Why should CIOs bet on unifying their data and AI practices? In 2024, departments and teams experimented with gen AI tools tied to their workflows and operating metrics.

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Cost-Benefit Data-driven Strategy Marketing 142

CIO Business Intelligence

SEPTEMBER 12, 2024

Zoho has updated Zoho Analytics to add artificial intelligence to the product and enables customers create custom machine-learning models using its new Data Science and Machine Learning (DSML) Studio. are across four key areas, the company said: data management, AI, data science and machine learning, and extensibility.

Analytics 131

Analytics Diagnostic Analytics Machine Learning Forecasting 131

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Data Science Data Analytics Prescriptive Analytics Analytics 76

datapine

NOVEMBER 27, 2019

You simply choose the data source you want to analyze and the column/variable (for instance, revenue) that the algorithm should focus on. Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smart Data Collective

NOVEMBER 26, 2021

Data analytics refers to the systematic computational analysis of statistics or data. Data analytics make up the relevant key performance indicators ( KPIs ) or metrics necessary for a business to create various sales and marketing strategies. When companies use data analytics, the processing of data is lightning fast.

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Marketing Data Analytics Key Performance Indicator Analytics 131

DataRobot Blog

JULY 28, 2022

This article presents a case study of how DataRobot was able to achieve high accuracy and low cost by actually using techniques learned through Data Science Competitions in the process of solving a DataRobot customer’s problem. Sensor Data Analysis Examples. The Best Way to Achieve Both Accuracy and Cost Control.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

datapine

MARCH 31, 2022

BI developer skills encompass crafting and executing data-driven queries upon request as well as the ongoing technical development of a company’s BI platforms or solutions. Here is a more specific rundown of BI developer skills: Demonstrable experience in the areas of BI development or data science. Yes, they exist.

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CIO Business Intelligence

MARCH 19, 2025

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

IT 59

IT Data Governance Data-driven Metrics 59

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

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Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Smart Data Collective

JUNE 16, 2022

Data science is both a rewarding and challenging profession. One study found that 44% of companies that hire data scientists say the departments are seriously understaffed. Fortunately, data scientists can make due with fewer staff if they use their resources more efficiently, which involves leveraging the right tools.

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Online Analytical Processing OLAP Analytics Data Warehouse 139

Cloudera

APRIL 9, 2021

The third video in the series highlighted Reporting and Data Visualization. Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. Cloudera’s Shared Data Experience (SDX) provides complete security and governance for models and the underlying data.

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Machine Learning Forecasting Manufacturing Predictive Analytics 98

Andrew White

JANUARY 12, 2021

Predicts 2021: Data and Analytics Strategies to Govern, Scale and Transform Digital Business : By 2024, 30% of organizations will invest in data and analytics governance platforms, thus increasing the business impact of trusted insights and new efficiencies. By 2024, 10% of digital commerce orders will be predicted and initiated by AI.

Analytics 144

Analytics Metadata Enterprise Data-driven 144

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Machine Learning Data Science Statistics Deep Learning 54

Data Science 101

OCTOBER 31, 2019

As taught in Data Science Dojo’s data science bootcamp , you will have improved prediction and forecasting with respect to your product. An in-depth analysis of trends can offer managers a much more reliable way to conduct planning and forecasts. Anomaly Detection.

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Data mining KDD Data Science Forecasting 77

DataRobot Blog

OCTOBER 18, 2022

The DataRobot expo booth at the 2022 conference showcased our AI Cloud platform with industry-specific demonstrations including Anti-Money Laundering for Financial Services , Predictive Maintenance for Manufacturing and Sales Forecasting for Retail. Today, his team is using open-source packages without a standardized AI platform.

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Big Data Forecasting Experimentation Machine Learning 96

CIO Business Intelligence

JULY 31, 2024

These models allow us to predict failures early, and we forecast a 20% reduction in furnace unplanned events, improving repair times by at least two days. We’ve also leveraged AI in the supply chain to revolutionize our demand forecasting and supply network planning. So AI helps us have fewer emergencies.

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Manufacturing Cost-Benefit Digital Transformation Forecasting 122

Smart Data Collective

JULY 23, 2021

The good thing is that you can overcome these recruitment hurdles by using big data and analytics. You can check out this website to know how data and performance metrics can improve real estate recruiting.). To strike the balance, recruiters and HR professionals need to develop data-driven hiring plans.

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Big Data Data-driven Metrics Advertising 108

Domino Data Lab

JUNE 2, 2019

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

CIO Business Intelligence

NOVEMBER 21, 2023

CIOs need a way to capture lightweight business cases or forecast business value to help prioritize new opportunities. The most successful programs go beyond rolling out tools by establishing governance in citizen data science programs while taking steps to reduce data debt.

IT 137

IT Risk Cost-Benefit Data Science 137

CIO Business Intelligence

AUGUST 9, 2024

Jon Pruitt, director of IT at Hartsfield-Jackson Atlanta International Airport, and his team crafted a visual business intelligence dashboard for a top executive in its Emergency Response Team to provide key metrics at a glance, including weather status, terminal occupancy, concessions operations, and parking capacity.

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Data Transformation Machine Learning Data Lake Dashboards 126

CIO Business Intelligence

JUNE 1, 2022

The company is applying winning insights from rapid, data-driven, evolutionary models versus relying on engine speed and aerodynamics alone to win races. Cloud-connected cars are now commonplace in the mainstream connected car market that is forecast to surpass $166 billion by 2025. billion by 2030. A Competitive Differentiator.

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Manufacturing Digital Transformation Predictive Analytics Strategy 119

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. Additionally, the AMPs catalog within CML is completely customizable, enabling your data science teams to build and securely share internal projects as AMPs. Structural Time Series.

Deep Learning 84

Deep Learning Machine Learning Forecasting Visualization 84

Dataiku

JULY 5, 2021

Reports and dashboards are used to review metrics, summaries, and forecasts, as well as to track trends. of them could be the key(s) to your next successful data science project. Visual analytics have become critical to the way that most of us do business. Read over these carefully, as one (or multiple!)

Forecasting 59

Forecasting Dashboards Metrics Visualization 59

Smart Data Collective

OCTOBER 14, 2019

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 billion allocated for data center systems and $90.2 These can help a developer find a career in the data science field.

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Big Data Software Data mining Prescriptive Analytics 99

Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. def get_neigbours(M, k): nn = NearestNeighbors(n_neighbors=k+1, metric="euclidean").fit(M) Using the adap learning algorithm to forecast the onset of diabetes mellitus. return synthetic.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

Birst BI

AUGUST 23, 2018

Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases?

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

DataRobot

JUNE 29, 2021

Imagine trying to forecast the demand for Clorox wipes back in January 2020 when all you have to go on is quantity sold in the last month or in the same period last year. The above image shows how forecasting bus rides in Chicago became incredibly hard in March of 2020 when everyone suddenly started to work from home. Over and over.

Machine Learning 80

Machine Learning Data Processing Forecasting Modeling 80

Sisense

AUGUST 14, 2020

Whether it’s core to the product, as with a stock market forecasting algorithm in Quants, or a peripheral component, such as a healthcare domain chatbot that diagnoses diseases via dialog with a patient, building reliable AI components into products is now part of the learning curve that product teams have to manage. .

Machine Learning 98

Machine Learning Visualization Predictive Analytics Testing 98

datapine

MAY 16, 2019

In summary, restaurant-based data analytics is crucial to the success of your restaurant because they enable you to: Organize your data and omit any metrics that are relevant to your goals. Transform your most valuable data into actionable insights. Forecasting trends.

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Analytics Predictive Analytics Advertising Dashboards 163

The Unofficial Google Data Science Blog

APRIL 19, 2021

To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. If, over the long run, it really did rain about 40 percent of the time, that means your forecasts were well calibrated.

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Modeling IT Metrics Testing 122

DataRobot

DECEMBER 16, 2021

But let me share a few useful and exciting methods that I have been using lately: Time series – new series modelers: One of the challenges that you can face when forecasting demand is how to work around products that are seasonal or are newly introduced. See How DataRobot Extends the Capabilities for Expert Data Scientists.

Forecasting 52

Forecasting Metrics Data Science Modeling 52

Smart Data Collective

NOVEMBER 7, 2019

Towards Data Science discusses some of the benefits of predictive analytics with employee retention. As a result, when we fit classifiers on such datasets, we should use metrics other than accuracy when comparing models such as f1-score or AUC (area under ROC curve).

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Predictive Analytics Analytics Cost-Benefit Risk 70

DataRobot

APRIL 29, 2021

This year’s theme of The Hunt for Transformational Growth is designed to help organizations unleash the power of enterprise AI to improve forecasts, generate actionable insights, and unlock exponential growth for businesses worldwide. This list includes: Rachik Laouar is Head of Data Science for the Adecco Group.

Machine Learning 59

Machine Learning Experimentation Data Science Data-driven 59

datapine

OCTOBER 14, 2020

An interactive dashboard is a data management tool that tracks, analyzes, monitors, and visually displays key business metrics while allowing users to interact with data, enabling them to make well-informed, data-driven, and healthy business decisions. Benefit from amazing interactive dashboards! 4) Cross Tab Filters.

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Dashboards Interactive Reporting KPI 235

Smarten

APRIL 24, 2019

Augmented Analytics allows organizations to integrate data from numerous data sources and to use that data to analyze and display results in a clear manner so the business can make unbiased decisions and establish objective metrics. Users can compare results against plans and forecasts.

Business Intelligence 0

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