Smarten

JULY 23, 2019

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

Smarten

JUNE 29, 2018

This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. What is ARIMAX Forecasting? This method is suitable for forecasting when data is stationary/non stationary, and multivariate with any type of data pattern, i.e., level/trend /seasonality/cyclicity. About Smarten.

Forecasting 40

Forecasting Enterprise IT Business Intelligence 40

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. For example, retailers can predict which stores are most likely to sell out of a particular kind of product. Those who work in the field of data science are known as data scientists.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

Smarten

JUNE 26, 2018

This article provides a brief explanation of the ARIMA method of analytical forecasting. What is ARIMA Forecasting? Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. p: to apply autoregressive model on series.

Forecasting 40

Forecasting Enterprise IT Sales 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

JANUARY 21, 2019

Time Series Forecasting. Holt-Winters Forecasting. Descriptive Statistics. ARIMA Forecasting. Chi Square Test. ARIMAX Forecasting. Paired Sample T Test. Dependent Sample T-Test. Independent Samples T Test. Consider the myriad of techniques used by data scientists and analysts!

Analytics 40

Analytics Predictive Modeling Forecasting Testing 40

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 59

Machine Learning Data Science Statistics Deep Learning 59

Smarten

DECEMBER 3, 2023

Solution capabilities included self-serve data preparation , smart data visualization and predictive analytics for forecasting, etc. Augmented Analytics Explained : As self-serve augmented analytics began to evolve, new tools and techniques were added, and business users now enjoy the expanded capabilities of predictive analytics.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

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.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

JULY 10, 2018

Use Case(s): Weather Forecasting, Fraud Analysis and more. Independent Samples T Test: What is the Independent Samples T Test Method of Analysis and How Can it Benefit an Organization? Paired Sample T Test: What is the Paired Sample T Test and How is it Beneficial to Business Analysis?

Analytics 40

Analytics Forecasting Statistics Sales 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). All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists. About Smarten.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Birst BI

AUGUST 23, 2018

For example, there are a plethora of software tools available to automatically develop predictive models from relational data, and according to Gartner, “By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.” [1]

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

JUNE 29, 2018

Weather Forecasting – Based on temperature, humidity, pressure etc., an organization can predict if it will be rainy/sunny/windy tomorrow. a business can predict the likelihood of fraud. It is useful for making predictions and forecasting data based on historical results. About Smarten.

Enterprise 40

Enterprise IT Business Intelligence Forecasting 40

Smarten

JULY 3, 2017

Advanced Data Discovery allows business users to perform early prototyping and to test hypothesis without the skills of a data scientist. Tools like plug n’ play predictive analysis and smart data visualization ensure data democratization and drastically reduce the time and cost of analysis and experimentation. Yay or Nay?

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

Smarten

JUNE 27, 2018

SVM Classification Analysis can be used for many analytical tasks: Credit/Loan Approval Analysis – Given a list of client transactional attributes, a business can predict whether a client will default on a loan. Medical Diagnosis – Given a list of symptoms, a doctor can predict if a patient has a particular disease.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

The KNN Classification algorithm is useful in determining probable outcome and results and in forecasting and predicting results, given the existence of multiple variables. About Smarten.

Enterprise 40

Enterprise Business Intelligence Predictive Modeling Statistics 40

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. Even then, some manual cleaning was needed (e.g.,

Risk 67

Risk ROI Modeling Metrics 67

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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

Jet Global

MAY 1, 2023

Healthcare is forecasted for significant growth in the near future. Head of Sales Priorities Make quota Get an accurate forecast Beat the competition Expand market share Facilitate customer success Connect the Dots Remember that the sales team is on the front lines. They can then pinpoint areas for improvement.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52