Five Patterns of Big Data Integration via @LakshmiLJ

Five Patterns of Big Data Integration via @LakshmiLJ - in this article by Lakshmi Randall on +Datafloq she discusses that as our reliance on Hadoop and Spark for data management, processing and analytics grows, data integration strategies should evolve to exploit big data platforms in support of digital business, Internet of Things (IoT) and analytics use cases.

I can imagine many are stuck thinking of the "old" was of integrating data and many processes and standards have not bee updated nor adapted for this new world of data integration.

Why You Should Keep Your Analytics Simple via @sisense

Why You Should Keep Your Analytics Simple via @sisense - in this article by Eran Levy in +Datafloq he discusses a research paper by renowned consultancy Aberdeen Group which reveals that “[data] complexity is often best answered with simplicity”. Several other surveys reveal interesting findings with regard to the costs and benefits of using an integrated tool for data preparation, querying and visualization, as opposed to the “assembly line” approach.

I think it is important to keep things as simple as you can to make it easier to understand and maintain going forward.

Why Cloudera is saying 'Goodbye, MapReduce' and 'Hello, Spark' via @FortuneMagazine

Why Cloudera is saying 'Goodbye, MapReduce' and 'Hello, Spark' via +Fortune Magazine  - in this article by Derrick Harris he describes why Cloudera are moving from MapReduce to Spark and the process/effect of doing that.

Interesting article and well worth the read

Full Clinical Benefit of Electronic Patient Records In Question via @infomgmt

Full Clinical Benefit of Electronic Patient Records In Question via +Information Management - Greg Slabodkin says while studies on the electronic exchange of health information show some evidence of benefits for healthcare, the full impact of HIE on improving clinical outcomes and avoiding potential harms has been inadequately studied and needs additional research.

This is a US based study and analysis.  From the UK side, there was a project to implement a centralised patient records system but it was cancelled in 2011 after countless delays and escalating costs. I have to say as a UK patient there are several issues that the centralised system could have resolved which I have personal experience of:

• Patient records are currently stored in local data silos and there is no information sharing between them.  I have MRI scans in 2 hospitals in different areas and there is no sharing of that data between them.
• Communication between clinicians seems to be via paper letter, which is scanned in as a document, but there appears to be no OCR applied to it to add meaningful data to the computer system.

There has to be some form of communication - whether that be an interface, a centralised database, or something else.

Buckle your Seats Belts. 2016 is the Year of Awesome Analytics via @infomgmt

Buckle your Seats Belts. 2016 is the Year of Awesome Analytics via +Information Management - according to Dan Graham demand for data scientists, power users, and architects will soar even higher in 2016. Corporations will compete for these experts but will not fill their gaps.

I can imagine that happening but we need to make sure the financial recovery is good enough for the investment. I realise that this is an invest or die kind of situation, but it needs to be a good enough investment, and not something on the cheap.

Beginners Tutorial on Conjoint Analysis using R via @AnalyticsVidhya

Beginners Tutorial on Conjoint Analysis using R by Sray Agarwal on +Analytics Vidhya - A technique that allows companies to do more in limited budgets & used widely in product designing? Its known as "Conjoint Analysis". In this article Sray explores this new concept together with a case study, using R, for beginners to get a grip easily.

I love this idea and having the examples in R means I understand it better.

Happy New Year

Happy New Year to everyone. Wishing you all a successful 2016 where you find even more innovative uses for data and analytics.

M x