Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Smarten

JUNE 29, 2018

The independent sample t-test is a statistical method of hypothesis testing that determines whether there is a statistically significant difference between the means of two independent samples. Based on this value, the grocery store manager can decide on its marketing strategies for better sales and increased revenue.

Testing 40

Testing Statistics IT Business Intelligence 40

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. BA primarily predicts what will happen in the future. What About “Business Intelligence”?

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Your marketing strategy is only as good as your ability to deliver measurable results. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

Smarten

JUNE 29, 2018

This article describes the analytical technique of multiple linear regression. Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X, and Y). What is Multiple Linear Regression Analysis? Use Case – 2.

Business Analysis 40

Business Analysis IT Sales Statistics 40

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. Linear Trend. Stationary/Stationarity.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

JUNE 26, 2018

Business Problem: A research agency wants to predict the likelihood of each election candidate being voted on by each voter and in turn devise a strategy to take proactive steps. Let’s look at two use cases: Use Case – 1.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 25, 2018

Sales team segments that are facing challenges based on any current discounting strategy can be identified and a deal negotiation strategy can be improved and optimized. Business Benefit: The business marketing team can focus on risky customer segments in an efficient way in order to avoid losing those customers.

Enterprise 40

Enterprise IT Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

The enterprise can also identify any gap between the targeted and estimated growth and develop an appropriate strategy to reduce this gap in order to achieve targets and results. Business Benefit: By analyzing the various combinations of predictor variables, the business can forecast product growth, trends, patterns and seasonality, if any.

Forecasting 40

Forecasting Enterprise IT Business Intelligence 40

Smarten

JUNE 27, 2018

In this example, the segments that have a response rate higher than the overall response rate can be targeted first since they will require less effort to convert to a purchase, whereas a different marketing strategy must be devised for the lower segments (segments that have a response rate less than the overall rate).

IT 40

IT Business Intelligence Predictive Modeling 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

datapine

MARCH 25, 2022

There is not a clear line between business intelligence and analytics, but they are extremely connected and interlaced in their approach towards resolving business issues, providing insights on past and present data, and defining future decisions. What Is Business Intelligence And Analytics?

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. temperature, salary).

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

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. Embracing Visual Data in Decision-Making Visual data plays an instrumental role in shaping decision-making processes and strategies across various domains.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

Smarten

JUNE 26, 2018

Business Problem: A retail store manager wants to conduct Market Basket analysis to come up with better strategy of products placement and product bundling. 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.

Business Intelligence 40

Business Intelligence Sales Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

Business Problem: A retail store manager wants to conduct Market Basket analysis to come up with a better strategy of product placement and product bundling. 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.

Business Analysis 40

Business Analysis IT Business Intelligence Sales 40

Rocket-Powered Data Science

OCTOBER 6, 2023

What is the point of those obvious statistical inferences? The point is that the 100% association between the event and the preceding condition has no special predictive or prescriptive power. How do predictive and prescriptive analytics fit into this statistical framework? ” “Just 26.5%

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Smarten

DECEMBER 5, 2022

Sample business use cases that relate to a team member role or responsibility, or an illustration of an analytical technique can allay user fears about the complexity of augmented analytics or about the real value of integrating an augmented analytics solution into the day-to-day workflow. Descriptive Statistics.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Testing 52

datapine

NOVEMBER 27, 2019

In 2020, BI tools and strategies will become increasingly customized. Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

DECEMBER 4, 2019

Predictive & Prescriptive Analytics. Predictive Analytics: What could happen? We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Approaches need to take this dynamic nature into mind.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 52

Data Analytics Analytics ROI Data Governance 52

Smarten

JUNE 21, 2018

Time series forecasting methods are used to extract and analyze data and statistics and characterize results to more accurately predict the future based on historical data. Business Benefit : If projected claims are lower than expected then proper marketing strategy can be devised to improve sales.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Alation

MAY 2, 2023

Data analytics techniques, such as machine learning (ML), artificial intelligence (AI), and predictive modeling, can help businesses extract valuable insights from this data to improve operations and customer experience. Meanwhile, predictive analytics enable them to analyze customer market trends.

Data Analytics 40

Data Analytics Analytics ROI Data Governance 40

Jet Global

MAY 1, 2023

You might price embedded analytics as an independent add-on, or you might upsell customers to a plan that includes analytics. Other money-making strategies include adding users in a per-seat structure or achieving price dominance in the market due. Explain how embedded analytics can deliver the capabilities customers need.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52