Hidden Insights

Analytics

Find out how analytics, from data mining to cognitive computing, is changing the way we do business

Analytics

Alena Tsishchanka23 January 2019 0

A roadmap for cultivating a data-driven culture

In my previous post, I suggested that it was possible to provide a road map that would help with the introduction of artificial intelligence, advanced analytics and machine learning into insurance companies. This post outlines the process. Start at the beginning The first area to address is applications where the

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Insurance

Analytics | Internet of Things

Federico Alberto Pozzi14 January 2019 1

How high-end fashion can benefit from better use of analytics

Fashion and analytics are not obvious partners. However, fashion is a business like any other, and like other businesses, it can benefit from understanding its customers better. Recent experience with one particular high-end fashion retailer suggests that good use of analytics, including predictive modelling, drawing on an end-to-end analytics platform,

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Retail

Analytics

Hidden Insights: Agile to active: The path from open source to open scalability

Biagio Grasso10 January 2019 0

Agile and active: scaling open source in the enterprise

For many organisations, open source supports the rapid and agile development of projects and models. New projects enable significant success with fast deployment of analytics projects, and also – importantly – supports a failing fast strategy without having to incur significant infrastructure costs. Deploying open source at the enterprise level

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Analytics

Andy Davies12 December 2018 0

Analytics in policing: it starts with data

In my first post I looked at the role of analytics in policing and how analytics could and should be used to benefit modern policing. However, a key point that can be forgotten is analytics is only as good as the data it is based on. It’s vital to have

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Government

Analytics

Why inventory optimisation is crucial for retailers

Aneshan Ramaloo11 December 2018 0

Why inventory optimisation is crucial for retailers

Retailers around the globe struggle to accurately forecast demand and, more importantly, optimise inventory levels. Consequently, this has a massive effect on bottom-line profitability. My last blog post focused specifically on the problem of “getting the size mix right” that retailers face and how advanced analytical techniques can provide a

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Retail

Analytics

Does your choice of programming language matter?

Paul Gittins6 December 2018 0

Does your choice of coding language matter?

I can still remember the emergence in the 1990s of Java as a universal and largely open-sourced programming language. Some observers believed it would signal the eventual demise of proprietary languages such as C, Fortran and Cobol. Current surveys, however, and there are many, confirm that plenty of people continue

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Analytics | Learn SAS

The Analytics Platform seen through Enterprise Architecture

James Ochiai-Brown5 December 2018 2

The Analytics Platform seen through Enterprise Architecture

Analytics is on every agenda – including Enterprise Architecture Data analytics and AI is now on the agenda of every organisation. After years of being the back-room preserve of analysts, it is now out in the open, in the boardroom and being proclaimed as central to business strategy and transformation.

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Analytics | Customer Intelligence

Vijayne Govender4 December 2018 0

The customer intelligence collection

If you want to get to grips with the topic of customer intelligence, who better to ask than David Cosgrave, who leads the SAS® Customer Intelligence team in South EMEA? Over the last few years, David has written a number of articles, and contributed to several others, on the subject

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Communications | Government | Retail

Analytics

Data Preparation in the Analytical Life Cycle

Ivor G. Moan3 December 2018 0

Understanding Data Preparation in the Analytics Life Cycle

What is Data Preparation and why does it matter? Data preparation is all the tasks involved in collecting, processing, and cleansing data for use in analytics and business intelligence. It therefore includes accessing, loading, structuring, purging, unifying (joining), adjusting data types, checking fields to see that only valid values are

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Blogs

Blogs

Analytics