Hidden Insights

Data Management

Blend, cleanse and prepare data for analytics, reporting, or data modernization efforts.

Artificial Intelligence | Data Management

The bigger AI challenge – governing data

Josefin Rosén15 August 2018 0

The bigger AI challenge – governing data

It is a truth universally acknowledged – if not always acted upon – that advanced analytics, and AI in particular, need data. What’s more, it needs lots of data, and it needs to be relevant and of good quality. Companies with access to more data tend to perform better, which

English

Analytics | Data Management

Hidden Insights: https://blogs.sas.com/content/sasdach/2018/08/06/10-dinge-die-ich-an-dir-liebe-cio-an-data-science-plattform/

Rainer Sternecker9 August 2018 0

"Ten things I love about you!" - The CIO to his data science platform

Analytics platforms have a lot to live up to. The scope may be fairly straightforward, but expectations can be high, and there is a wide range of users and customers, all of whom have slightly different needs. This post explores what IT decision makers can expect from an analytics platform.

English

Data Management

Business Analytics Portugal24 July 2018 0

Sete dicas para criar uma estratégia de governação de BI Self-service

As ferramentas analíticas de BI self-service estimulam os utilizadores com formas fáceis de obter respostas, orientadas por dados, a questões de negócio. Por outro lado, os sistemas corporativos tornaram-se uma marca registada da inteligência de negócio porque resolvem questões importantes, como a qualidade, consistência e governação aprimorada dos dados. As

Portuguese

Advanced Analytics | Data Management

Hidden Insights: Are you paying enough attention to data engineering tasks?

Ivor G. Moan4 July 2018 0

Are you paying enough attention to data engineering tasks?

Data science is hot. Being a data scientist has been described as one of the world’s sexiest careers – though that may say more about the people coining the description than data science – and data scientists are both in high demand and increasingly well-paid. It is, in fact, highly

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Analytics | Data Management

Lee Thorpe21 June 2018 0

IFRS 17 – the long road to compliance

When your industry is going to be turned on its head by something, the sooner you can start planning – or at least thinking about it – the better. The new International Financial Reporting Standard 17 (IFRS 17) will come into force in January 2021, and it’s set to completely

English

Insurance

Analytics | Artificial Intelligence | Data Management

Hidden Insights: Calling Dr. Data: Unlocking AI’s potential for the NHS

Mark Frankish4 June 2018 0

Calling Dr. Data: Unlocking AI’s potential for the NHS

The NHS is one of the UK’s most beloved institutions, but it’s also in need of some new thinking. This is especially true when it comes to technology. The first major wave of investment in artificial intelligence (AI) has seen entire industries transformed by the speed and capabilities of machine

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Health Care

Data Management

With GDPR deadline fast approaching, less than half ready for audit

Michael Herrmann24 May 2018 1

With GDPR deadline fast approaching, less than half ready for audit

The deadline is looming. The new regulation will be a trial by fire for interactions with customers, colleagues and regulatory authorities. Are you ready for this? And what has your company done to prepare? At SAS, we wanted to get a feel for where people are, so we conducted a

English

Data Management

Helmut Plinke24 May 2018 0

Will GDPR disrupt analytics?

The General Data Protection Regulation, or GDPR, comes into force on 25 May 2018. It has been a topic of considerable interest recently, and particularly its likely effect on individual sectors or business areas such as marketing and sales. Software manufacturers and consulting companies have been developing and launching solutions

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Advanced Analytics | Data Management

Hidden Insights: GDPR is affecting model deployment - how to deal with it

Mathias Lanner23 May 2018 0

GDPR is affecting model deployment - how to deal with it

Model deployment is a crucial part of the model life cycle. Having developed and validated your model, you need to be able to put it to work. This “putting to work” stage is called deployment, and it is far from trivial. At this stage, the model ceases to be “training”

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Blogs

Blogs

Data Management