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Top 5 Predictive Analytics Use Cases in the Retail Industry

Acuvate

Let’s study the following use cases which are currently in use in various leading retails companies to have better understanding of the value of predictive analytics in the retail industry. Predictive Analytics Use Case in the Retail Industry #1. Predictive Analytics Use Case in the Retail Industry #2. Download Now.

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The What, Why and How of Trade Promotion Forecasting

Acuvate

Trade Promotions are a crucial part of the consumer packaged goods (CPG) industry. 3) Big Data Integration. Being able to navigate, correlate and analyse vast troves of raw data in various formats should be a key feature of the tool. Enough to accommodate the current and future needs as the data sets expand.

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Infographic – 5 trends that will revolutionize the energy market in the next few years

mjvinnovation

See our infographic below, which is downloadable! The priority is to invest in the creation of a Digital DNA in order to meet the industry’s biggest challenges: climate change | shortage of resources | search for greater energy efficiency. Blockchain tops the list of drivers for industry change. The Action Plan.

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Data Science: what it is and how to start using it

mjvinnovation

Data scientists are trained to identify data that stands out in some way or form. This requires the identification of valuable data and the option to delete data that adds nothing to the strategy (for a specific project or the business as a whole). Is your company ready to make use of Data Science?

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Understanding the Innovation Landscape needed for Enabling Technologies in the World’s Energy Transition

Paul Hobcraft

IRENA’s Innovation Landscape report highlights innovations in enabling technologies and explored explicitly in the following briefs, where you go automatically to the download: Utility-scale batteries. Artificial Intelligence and Big Data. degree C above pre-industrial levels. Behind-the-meter batteries. Blockchain.

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7 steps to implement Data Science in your company

mjvinnovation

Also, you must keep up to date with the industry’s general landscape, including trends, risks, and opportunities. Within your core business and the objectives outlined for your Data Science strategy, there are several tools for the job. Data visualization is one of the most important parts of Data Science.

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A better way: combining Business Intelligence with Design Thinking

mjvinnovation

Big Data: data analysis is what really matters. The available data is not only useful for outlining a consumer profile on the internet. In the movie Moneyball, for example, a coach facing the challenge of running a low-budget baseball team decides to employ data analysis to improve the performance of his players.