IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. Business users will also perform data analytics within business intelligence (BI) platforms for insight into current market conditions or probable decision-making outcomes.

Data Science 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. There are a number of tools available on the market, and knowing which one to choose to increase performance can be time-consuming, and often confusing. Source: RStudio.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smarten

JULY 23, 2019

What is Predictive Analytics and How Can it Help My Business? What is predictive analytics? Put simply, predictive analytics is a method used to forecast and predict the future results and needs of an organization using historical data and a comprehensive set of data from across and outside the enterprise.

Modeling 63

Modeling Predictive Analytics Predictive Modeling IT 63

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

DataRobot Blog

JULY 28, 2022

Initially, the customer tried modeling using statistical methods to create typical features, such as moving averages, but the model metrics (R-square) was only 0.5 The larger the value, the better the model represents the data, and the smaller the value, the less well it represents the data. Accuracy before noise removal.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Smarten

JUNE 20, 2018

The business can use this information for forecasting and planning, and to test theories and strategies. In prediction, the objective is to “model” all the components to some trend patterns to the point that the only component that remains unexplained is the random component. Stationary/Stationarity. About Smarten.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

NOVEMBER 19, 2018

Today’s self-serve predictive analytics and forecasting tools are designed to support business users and data analysts alike. What is Predictive Analytics? Predictive analytics is the process of forecasting or predicting business results for planning purposes.

Business Objectives 40

Business Objectives Predictive Analytics Analytics Forecasting 40

Smarten

JUNE 29, 2018

Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X, and Y). For instance, if promotions and holiday seasons are significant factors, these factors should be given more focus when devising a marketing strategy. What is Multiple Linear Regression Analysis?

Business Analysis 40

Business Analysis IT Sales Statistics 40

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

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. Our team does a lot of forecasting. It also owns Google’s internal time series forecasting platform described in an earlier blog post.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Most BI software in the market are self-service.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available.

Machine Learning 74

Machine Learning Modeling Deep Learning Predictive Modeling 74

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. Satisfying customer needs and securing solvency in volatile markets both require quick decisions and decisive action. . Markets and competition are constantly becoming more dynamic.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

MARCH 16, 2021

Markets and competition today are highly dynamic and complex, and the future is characterized by uncertainty – not least because of COVID-19. Satisfying customer needs and securing solvency in volatile markets both require quick decisions and decisive action. . Markets and competition are constantly becoming more dynamic.

Forecasting 52

Forecasting Management Uncertainty Predictive Modeling 52

BI-Survey

JANUARY 29, 2023

Companies are therefore looking for ways to produce their plans and forecasts in less time, with less effort and with better results, because in a volatile market environment characterized by crises, there can no longer be “business as usual”, even in corporate planning. This also increasingly applies to forecasts and simulations.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

BI-Survey

NOVEMBER 24, 2020

This generates significant challenges for organizations in many areas and corporate planning and forecasting are no exceptions. The aim is to relieve planners and use historical data for valuable forecasts of the future. Planning, forecasting and analytics must be adapted to keep up with these demands.

Forecasting 94

Forecasting Predictive Modeling Statistics Data-driven 94

Smarten

JULY 10, 2018

Use Case(s): Weather Forecasting, Fraud Analysis and more. Use Case(s): Market Basket Analysis, Frequently Bundled Products and more. Use Case(s): Predict if loan default based on attributes of applicant; predict likelihood of successful treatment of new patient based on patient attributes and more.

Analytics 40

Analytics Forecasting Statistics Sales 40

FineReport

APRIL 24, 2024

This simplification allows stakeholders to grasp the underlying patterns and trends within the data without getting lost in the complexity of raw numbers and statistics. Interactive Dashboard created by FineReport Book A Demo These are just a few examples of the diverse range of data visualization tools available in the market today.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

Insight

FEBRUARY 19, 2020

Photo by Roberto Nickson on Unsplash Much effort has been spent understanding and forecasting the success of movies (e.g., Arthur de Vany’s Hollywood Economics and Kaggle’s recent box office prediction challenge ) and current attempts are using increasingly sophisticated techniques. part of what makes this so difficult!

Risk 67

Risk ROI Modeling Metrics 67

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. What is the point of those obvious statistical inferences?

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Smarten

JULY 9, 2018

Create Citizen Data Scientists with Assisted Predictive Modeling! You need Assisted Predictive Modeling (Plug n’ Play Predictive Analysis with auto-suggestions and recommendations). The Plug and Play Predictive Analytics and predictive modeling platform is suitable for business users.

Predictive Modeling 40

Predictive Modeling Modeling Predictive Analytics ROI 40

Smarten

OCTOBER 9, 2018

Today, predictive analytics is, and must be, accessible to business users, if your enterprise is to grow and respond to the need for data democratization and increased productivity within the enterprise and to the rapid changes in the market, competition, resource and supplier needs and customer buying behavior.

Predictive Analytics 40

Predictive Analytics Analytics Predictive Modeling Forecasting 40

datapine

NOVEMBER 27, 2019

Then, calculations will be run and come back to you with growth/trends/forecast, value driver, key segments correlations, anomalies, and what-if analysis. However, businesses today want to go further and predictive analytics is another trend to be closely monitored. It’s an extension of data mining which refers only to past data.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JULY 3, 2017

When an enterprise selects a self-serve business intelligence solution with Advanced Data Discovery , Smart Data Visualization , Plug n’ Play Predictive Analysis and Self-Serve Data Preparation , it can create an environment where business users are empowered and become greater assets to the organization. Yay or Nay?

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. What is the Holt-Winters Forecasting Algorithm? The Holt-Winters algorithm is used for forecasting and It is a time-series forecasting method. 2) Double Exponential Smoothing Use Case.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Smarten

DECEMBER 3, 2023

Maybe you just want to understand the analytics solution market better. Just as with any other software or technology evolution, the analytics solution market has changed. When these tools were introduced to the market, they provided support for the first iteration of a Citizen Data Scientist approach.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

datapine

DECEMBER 4, 2019

Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. In fact, the market size is expected to reach $6.0 in the last 5 years.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Data Science and Beyond

JANUARY 8, 2017

And how can you calculate your customer lifetime value correctly, avoiding the traps set up by clever search engine marketers? Second, given Google’s near-monopoly of the search market, if a page ranks highly for popular search terms, it is likely to become more popular and be seen as credible. Read on to find out!

Statistics 100

Statistics Modeling Predictive Modeling Marketing 100

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 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. Analyzing historical transaction data in financial reporting can help identify market trends and investment opportunities.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52