DataRobot

OCTOBER 19, 2021

Many available forecasts provide less than four weeks notice at the state and county level. Additionally, these forecasts often miss surges in community transmission until it is too late to change course. Traditional predictive models do not account for anomaly detection on data reporting issues (e.g.,

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 98

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. This includes trust in the data, the security, the brand and the people behind the AI.

B2B 68

B2B Interactive Optimization Forecasting 68

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

DataRobot

NOVEMBER 24, 2021

Whatever its requirements, applying data-driven AI strategies can help. Putting sensors into all of its wind turbines enabled GE to stream operational data to the cloud. Improve Supply Chain Logistics by Making Better Predictions. Model production time dropped from two days to five minutes. percent. .

Cost-Benefit 98

Cost-Benefit ROI Data-driven Predictive Modeling 98

IBM Big Data Hub

MAY 6, 2024

Optimize protocols using historical and synthetic data Complex and stringent protocols are notorious for delaying clinical trials and eroding patient engagement. Diving deep into historical trial data with a protocol complexity rating also reveals golden insights, especially around patient-centric elements.

Advertising 69

Advertising Data-driven Optimization Strategy 69

IBM Big Data Hub

OCTOBER 5, 2022

Build planning models to improve supply chain management. You also build planning models to capture relationships and constraints so that you can change your driver assumptions and immediately see the impact on resources and capacity over time. The challenge faced by every company is matching supply with demand.

Analytics 52

Analytics Forecasting Predictive Modeling Manufacturing 52

Sisense

JANUARY 26, 2020

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. Building an accurate predictive analytics model isn’t easy. It requires a skilled data team, advanced tools, and enormous amounts of clean data from the right combination of inputs.

Predictive Analytics 78

Predictive Analytics Manufacturing Analytics Forecasting 78

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

DataRobot Blog

AUGUST 10, 2022

Change is happening fast across the NHS with the focus squarely on harnessing the huge amount of data the NHS generates — to drive forward the transformation programmes needed to address the backlog for elective care and growing demands for services. Enabling population health management and reducing health inequalities.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

Sisense

MARCH 7, 2021

To get truly powerful insights, you need to pull in data from multiple sources. Additional data sources increase your chances to inform actions, fueling top-line and bottom-line growth. Measuremen: Optimizing facilities use with data from numerous sources. Since those early days, Measuremen has broadened its data sources.

Slice and Dice 98

Slice and Dice Data-driven Cost-Benefit Forecasting 98

IBM Big Data Hub

FEBRUARY 14, 2024

Promote cross- and up-selling Recommendation engines use consumer behavior data and AI algorithms to help discover data trends to be used in the development of more effective up-selling and cross-selling strategies, resulting in more useful add-on recommendations for customers during checkout for online retailers.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Smarten

NOVEMBER 22, 2019

Why is Data Literacy Important? If you have attended technology conferences or read industry publications, you have probably heard the term ‘Data Literacy’. Data Literacy means that your team members have the ability to read, work with and understand, analyze, present and make decisions using data.

Predictive Modeling 67

Predictive Modeling Data-driven Forecasting Visualization 67

Sisense

SEPTEMBER 9, 2019

Mark’s team is constantly adapting to and meeting the challenges of a rapidly evolving business using cloud technologies, real-time analytics, data warehousing, and virtualization. What if we could use this data to focus our resources and deliver better products? Using Sentiment Analytics to Inform New Product Design Decisions.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

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? One challenge in applying data science is to identify pertinent business issues.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 50

Machine Learning Marketing Forecasting Modeling 50

Jedox

JULY 23, 2019

You do not have to be a data scientist to recognize the impact of technology on FP&A is and will continue to be significant. These are often not “out of the box” solutions and will require us to spend time learning new skills in process automation, analytics and financial modeling. Once cleansed, its possible to enrich the data.

Technology 52

Technology Forecasting Finance Data-driven 52

FineReport

APRIL 9, 2024

Understanding Healthcare BI Tools The Role of Healthcare BI Tools Healthcare BI tools are instrumental in revolutionizing decision-making processes and patient care through the utilization of advanced data analysis and technology.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

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.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Jet Global

APRIL 27, 2020

More than just crunching the numbers, the modern retail CFO now needs to be at the forefront of technology , leading how retailers collect and use their data—especially in financial planning. Modern retail financial planning requires data agility and the support of the CFO’s office in taking on a more flexible approach.

Finance 52

Finance Forecasting Sales Reporting 52

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

Rocket-Powered Data Science

JULY 13, 2023

Data is more than just another digital asset of the modern enterprise. So, what happens when the data flows are not quarterly, or monthly, or even daily, but streaming in real-time? So, what happens when the data flows are not quarterly, or monthly, or even daily, but streaming in real-time? It is an essential asset.

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

DataRobot

OCTOBER 15, 2021

At DataRobot, our engineers and data scientists are thinking about how to harness the power of AI and ML to reduce our carbon footprint, detect where unintended energy emissions may occur, predict anomalous and dangerous weather, and ensure we always have enough energy to meet our needs. Conclusion.

Forecasting 93

Forecasting Data-driven Predictive Modeling Modeling 93

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high.

Insurance 78

Insurance Risk Data-driven Finance 78

DataRobot

NOVEMBER 15, 2021

These solutions are designed to integrate intelligent insights into data platforms, applications, and systems integrator services that provide customers with the critical capabilities they need to accelerate growth, operate at scale and meet the specific challenges facing their industry. Find out more.

Manufacturing 52

Manufacturing Forecasting Machine Learning Data-driven 52

BI-Survey

MARCH 16, 2021

Corporate planning and forecasting needs to be carried out efficiently, in shorter cycles and must be updated quickly for well-founded decision-making. This results in growing competitive pressure, driven by innovation, complexity and changing social and political conditions. Digitalization is a key driver in this respect.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

MARCH 16, 2021

Corporate planning and forecasting needs to be carried out efficiently, in shorter cycles and must be updated quickly for well-founded decision-making. This results in growing competitive pressure, driven by innovation, complexity and changing social and political conditions. Digitalization is a key driver in this respect.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

NOVEMBER 24, 2020

This generates significant challenges for organizations in many areas and corporate planning and forecasting are no exceptions. In addition, the use of predictive technologies and algorithms for corporate planning is gaining in significance in many organizations.

Forecasting 94

Forecasting Predictive Modeling Statistics Data-driven 94

FineReport

APRIL 24, 2024

What is Data Visualization Understanding the Concept Data visualization, in simple terms, refers to the presentation of data in a visual format. By utilizing visual elements, data visualization allows individuals to grasp difficult concepts or identify new patterns within the data.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

IBM Big Data Hub

JULY 5, 2023

Asset lifecycle management (ALM) is a data-driven approach that many companies use to care for their assets, maximize their efficiency and increase their profitability. Data management and storage requirements vary widely from country to country and are constantly evolving.

Strategy 55

Strategy Management IoT Cost-Benefit 55

Rocket-Powered Data Science

SEPTEMBER 20, 2021

The way that I explained it to my data science students years ago was like this. I brought them deeper into the world by pointing out how much more effective and efficient the data professionals’ life would be if our data repositories had a similar semantic meta-layer. What is a semantic layer? There’s more.

Data Science 286

Data Science Forecasting Business Intelligence Sales 286

Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. This is predictive power discovery. These are primarily forward-looking actionable (proactive) applications.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

DataRobot Blog

JUNE 24, 2022

Many real estate players have long made decisions based on intuition coupled with analyzing traditional key retrospective data. Next to this ongoing challenge of compiling and interpreting data, real estate players are also dealing with the challenge that real estate is increasingly driven by human needs and market shifts.

Forecasting 52

Forecasting Machine Learning Marketing Data-driven 52

DataRobot

JANUARY 20, 2022

The following is a summary list of the key data-related priorities facing ICSs during 2022 and how we believe the combined Snowflake & DataRobot AI Cloud Platform stack can empower the ICS teams to deliver on these priorities. Key Data Challenges for Integrated Care Systems in 2022. Building data communities.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

Cloudera

JANUARY 25, 2022

As roles within organizations evolve (as seen by the growth of citizen scientists and analytics engineers) and as data needs change (think schema changes and real-time), we need more intelligent ways to perform visual exploration, data interrogation, and share insights. Create the Predict Function.

Visualization 87

Visualization Machine Learning Predictive Analytics Data-driven 87

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JUNE 14, 2019

What is Natural Language Processing (NLP) Driven Analytics? NLP allows the enterprise to expand the use of business intelligence across the enterprise by offering business users an intuitive tool to ask for and receive crucial data and to understand the analytical output and share it with other users. Part 3 of 3 articles).

Cost-Benefit 40

Cost-Benefit IT Predictive Modeling Business Intelligence 40

Smarten

JULY 19, 2017

To be successful in business, every organization must find a way to accurately forecast and predict the future of its market, and its internal operations, and better understand the buying behavior of its customers and prospects.

Business Intelligence 40

Business Intelligence Predictive Modeling Cost-Benefit Data-driven 40