Smart Data Collective

OCTOBER 31, 2021

When creating a business plan, you should think about the challenges you cannot accomplish without a good strategy and what strategy would work best to address them. You will find that analytics will make these processes much easier. Selecting a segment with analytics. Price segment for goods.

Analytics 109

Analytics Data mining Analytics Technologies Sales 109

datapine

JANUARY 6, 2022

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

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

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

Business Benefit: The business marketing team can focus on risky customer segments in an efficient way in order to avoid losing those customers. 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.

Enterprise 40

Enterprise IT Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

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

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. What’s the difference between Business Analytics and Business Intelligence?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

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

datapine

MAY 16, 2019

A sobering statistic if ever we saw one. Here, we will look at restaurant data analytics, restaurant predictive analytics, analytics software for restaurants, and the specific ways that big data can help boost your business prospects across the board. Why Are Restaurant Analytics Important?

Analytics 163

Analytics Predictive Analytics Advertising Dashboards 163

datapine

AUGUST 29, 2022

At 156 pages on Kindle, this is a book you could finish in one (long) sitting if you were so inclined, and that you can also use as an inspiration when you work on your business intelligence strategy. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Grooper

AUGUST 19, 2019

Successfully navigating the 20,000+ analytics and business intelligence solutions on the market requires a special approach. Read on to learn how data literacy, information as a second language, and insight-driven analytics take digital strategy to a new level. Applied Analytics. Business Analytics.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

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

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. Business Benefit: The darker segments reveal the ideal methods of product bundling and placement to increase cross-sales. Use Case – 1.

Business Intelligence 40

Business Intelligence Sales Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

To understand the value of this applied technique, let’s consider two business use cases. 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. Use Case – 1.

Business Analysis 40

Business Analysis IT Business Intelligence Sales 40

datapine

NOVEMBER 27, 2019

But the BI landscape is evolving and the future of business intelligence is played now, with emerging trends to keep an eye on. In 2020, BI tools and strategies will become increasingly customized. Source: Business Application Research Center *. Share the essential business intelligence trends among your team!

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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 Problem : Insurance claim manager wants to forecast policy sales for next month based on past 12 months data.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40