Smart Data Collective

SEPTEMBER 7, 2021

Such predictive analytics can help to define what products will spike the biggest interest of the audience. With predictive analytics and real-time information about products, retailers can avoid supply shortages, optimise the storage facility so that most popular items are easy to reach, etc. Setting the optimal prices.

Retail 326

Retail Big Data Predictive Analytics Digital 326

Smart Data Collective

APRIL 20, 2019

We can draw a similar conclusion about the relevance of business cards in 2019. Data Floq made this point clear in a post they made in 2016. Using predictive analytics to continually update business cards. Predictive analytics is one of the most useful advances in big data.

Big Data 208

Big Data Predictive Analytics Monitoring Visualization 208

Smart Data Collective

DECEMBER 19, 2019

© Statista 2019 Also, here is a list of some other stats. In 2016, A Facebook bot tricked more than 10,000 Facebook users. Identifying malicious activities and threats much before using advanced predictive analytics. Or it is a pure blessing using which we can overcome the data security issues?

Artificial Intelligence 160

Artificial Intelligence Cybersecurity Data Security Predictive Analytics 160

Data Pine

NOVEMBER 19, 2019

While we’ve seen traces of this in 2019, it’s in 2020 that computer vision will make a significant mark in both the consumer and business world. Already in our shortlist of tech buzzwords 2019, artificial intelligence is on the front scene for next year again. Artificial Intelligence (AI). Connected Retail. Hyperautomation.

Artificial Intelligence 111

Artificial Intelligence Vision Banking Retail 111

ElegantJ BI

JUNE 15, 2022

Ask a question that reveals ‘most’ or ‘least’, ‘high’ or ‘low’: What was the highest temperature in Arizona in 2019 and when did it happen? Ask a question about a point in time without the need for specific dates: How many silk blouses were sold during Christmas season in 2016 vs. 2018?

Retail 130

Retail Finance Predictive Analytics Business Intelligence 130

ElegantJ BI

JUNE 15, 2022

Ask a question that reveals ‘most’ or ‘least’, ‘high’ or ‘low’: What was the highest temperature in Arizona in 2019 and when did it happen? Ask a question about a point in time without the need for specific dates: How many silk blouses were sold during Christmas season in 2016 vs. 2018?

Retail 130

Retail Finance Predictive Analytics Business Intelligence 130

ElegantJ BI

JUNE 15, 2022

Ask a question that reveals ‘most’ or ‘least’, ‘high’ or ‘low’: What was the highest temperature in Arizona in 2019 and when did it happen? Ask a question about a point in time without the need for specific dates: How many silk blouses were sold during Christmas season in 2016 vs. 2018?

Retail 130

Retail Finance Predictive Analytics Business Intelligence 130