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Many companies have invested significantly in gathering vast amounts of data, yet they still struggle to extract insights, put them to work for the business and create truly data-driven organisations. The virtuous circle of data explores how organisations can spark a chain of events through top-down leadership and bottom-up employee engagement that creates a culture with data at the centre of decision-making.

Many companies have invested significantly in gathering vast amounts of data, yet they still struggle to extract insights, put them to work for the business and create truly data-driven organisations. The virtuous circle of data explores how organisations can spark a chain of events through top-down leadership and bottom-up employee engagement that creates a culture with data at the centre of decision-making.

Finding useful knowledge nuggets amongst the torrents of data is a skill in itself. Creating insightful stories that bring the data to life is an emergent skill practiced by data journalists. An excellent article with lots of useful references for anyone who aspires to blend data analytics with storytelling.

Whilst advocating the use of storytelling to illustrate key facts in data, the article highlights the detrimental side of storytelling, which can undermine good decision making. When we are trying to build a story from data we fail to recognize that most stories we are supposed to glean from data cause cognitively dissonance.

Ensuring that big data creates big value calls for a reskilling effort that is at least as much about fostering a data-driven mindset and analytical culture as it is about adopting new technology. Companies leading the revolution already have an experiment-focused, numerate, data-literate workforce. Are you ready to join them?

Every industry is becoming an analytics industry because of the inclusion of data-driven technology. Traditional industries, such as healthcare and finance, are actually purchasing analytic technologies with the intent of becoming digital leaders in their industry. IoT is regarded as a future trend, and according to Gartner, by 2018, six billion connected things will be requesting data support. This requires tools that are future-proofed to handle the mass and types of data that Gartner is forecasting.

Data should be Findable Data should be Accessible Data should be Interoperable Data should be Re-usable

n today's digital era, governments across the globe are amassing larger amounts of data than ever before. Some of this is structured data such as census records, phone numbers, addresses, and any information that can easily be entered into a database or spreadsheet. And some of it is unstructured data, or harder-to-analyze information such as emails, documents, web pages, photos, and videos.

"By capturing the big data on user activity and using this data to create a more engaging experience, businesses can better engage and motivate employees. As many at Dreamforce 2013 learned, combining big data with gamification is a powerful tool for motivating better performance, driving business results, and generating a competitive advantage."

Big data is now moving from the sole care of data scientists and becoming accessible to employees throughout organizations. The mystique surrounding data analytics is falling away, with tools designed to let non-technically-minded people understand metrics.

Worth downloading and reading this paper. One abstract: "The ultimate goal is to enable data scientists,business analysts and other users "to extract the most information they can out of data as quickly as possible....For the business, we need answers now. The market is fixing the pace, so we have to give the best answer we can at the right time."

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

"Born and raised in Sweden, Anna Rosling-Rönnlund is a visionary whose main goal in life is to find systematic sense in vast amounts of data. As tons of data concerning the health and economic status of each country is collected annually, Anna's focus is to make this global public data easier to understand and utilize"

"The "big data, little brain" phenomenon is defined as managers who rely excessively on data to guide their decisions, abdicating their knowledge and experience."

"The tech giants are preparing for a stringent new set of data privacy rules in the region, called the General Data Protection Regulation."

The new rules generally expand the definition of personal data - so it can include information such as location data, online identifiers (such as IP addresses) and other metadata. So again, this means businesses really need to conduct an audit to identify all the types of personal data they hold. Ignorance is not compliance.

The challenge for the 21 century is to say, OK we've got the devices which can collect and store this data, but what shall we do with that data and what are the advantages of understanding that data, will it help us navigate society better and to help us improve the way that we live? And there are lots of different aspects to working that out.

"The ability for machines to see, understand and interact with the world is growing at a tremendous rate and is only increasing with the volume of data that helps them learn and understand even faster. Big data is the fuel that powers AI."

Curated website of all things about Big Data, Analytics etc.

IBM - Watson Analytics and Prediction Engine

I set up this website in order to experiment with the emerging Semantic Web and Linked Data Web. I'm not really interested (at this stage) in creating a pretty website so please forgive the amateurish look of these pages. Maybe I'll change this with time, but for now I'm more interesting in what's going on under the bonnet and for now it's all about the RDF. These pages are best viewed in Firefox. To get the most from these pages there are a number of addons you can install to transform your web browswer into a semantic web browser: Semantic Radar - a simple plugin that detects semantic web technologies on a webpage Operator - lets you do cool stuff with microformats and RDFa Tabulator - a neat way to browse RDF and linked data on the semantic web OpenLink Data Explorer - another data browser for the semantic web Welcome, and enjoy... Feedback Diigo Web Highlighter (v1.6.2.4)  Highlight     Bookmark   Sticky Note Share Save Bookmark Url Title PrivateRead laterCache Description Tags Loading recommended tags... Add to a List Share to a Group Share my existing annotations