By David Geere Pricing is of key importance for any business. Setting the right price for your products and services can play a big part in your success or failure (even if you’re a not-for-profit) and it’s incredibly sensitive. Research suggests that a small increase in price can bring a...
By Cathy Wilks A recent survey predicted that by the end of 2016, fewer than 25% of technology jobs in developed countries will be held by women, slightly down on the proportion for 2015. The study suggested a number of reasons for the low take-up of technology jobs by women,...
By Tom Middleton In the fourth vlog in our series from the 'Our Lives in Data' exhibition at the Science Museum, we've experimented with the data mirror which is one of the most fun elements of the exhibition. Tom Middleton, from our Risk Assurance team, talks about the different technologies...
If you read the first part of this series you’ll undoubtedly have been on the lookout for Data Governance banana skins and with any luck, will have avoided a few slips!
In this blog I’ll talk about the silver bullet that will (apparently) resolve all data-related issues in one go – the Enterprise-wide Data Governance initiative. This subject deserves all the airtime it can get – it’s where most programs fail before they even begin.
Every time you use a search engine, land on a website, buy a product or download an app, you generate and share personal data via a sophisticated and sometimes covert combination of tracking tools like cookies, beacons and e-tags.
This expansion in personal data collection is creating enormous visibility into individual lives, preferences and behaviors, a trend that will escalate as technology continues to evolve with breakthroughs such as wearable devices, autonomous automobiles and the Internet of Things.
The proliferation of data also represents a potential treasure trove of opportunity for companies seeking new sources of revenue and competitive advantages. In fact, 64% of respondents to PwC’s 20th Annual Global CEO Survey
By Triin Sober
Bots have been getting a bad rep in the news recently. You may have seen articles on ticket touts using botnets to buy up tickets to concerts and events only to sell them on to fans at extortionate prices or smart devices connected to the internet of things being used in cyber attacks. But do we really know what bots are and can they be put to a better use?
By Maaike Platenburg
We hear a whole lot about big data these days. For many people, “big data” means a flood of data, but what exactly is it? According to UN Global Pulse, information can be defined as “big data” when the data volume can no longer be managed with normal database tools. Big data is typically characterised by the 3Vs: volume of data, variety of types of data and the velocity at which the data is processed. Big data comes in different ways and can be divided in structured data and unstructured data.
By Rav Hayer and James Drury-Smith
The General Data Protection Regulation (GDPR) will put individuals in control of their personal data, empowering them to choose how (and whether) businesses use their data. Where personal data is not treated correctly, individuals will have increased rights to legal recourse and can, in some instances, claim compensation. Regulators across the EU will have unprecedented power to enforce the legislation and impose hefty fines in instances of non-compliance.
By Jon Cooke
Data lakes, as I said in my previous blog, are the latest buzz word in analytics. While I warned about jumping into the world of data lakes without thinking carefully about what you want to achieve, I do believe that these data depositories are the long-term future. They have a clear advantage over data warehousing because they offer a non-relational way of looking at your data
By Ben Whittingham and David Doyle
Transport generates multiple sources of data, and it’s often being used real time.
In the third vlog in our series from the 'Our Lives in Data' exhibition at the Science Museum, we've focused on the transport section which displays the inside an Oyster Card reader and a 3D model of Bond Street station.
By Kiran Gill
Data Governance banana skins - n sudden, unexpected and sometimes creates embarrassing Data Governance situation, often causing difficulty in realising long-term governance success.
Data Governance banana skins can be easily side-stepped or comprehensively planned for if you know what to look out for in advance.
By Jon Cooke
It’s a feature of developing technology that buzz words tend to appear all of a sudden – everyone is talking about it. At the moment it’s ‘data lakes’, a method of storing Big Data – for which Apache Hadoop is the best-known platform.
By Paul Delbridge
In early November, a leading UK personal lines insurer announced the launch of an app that would use Facebook data to “better understand first time drivers and more accurately predict risk”. This was intended to award discounted premium rates to safer drivers, who would be identified on the basis of specific personality profiles. Shortly afterwards, Facebook announced that this contravened its privacy policies, triggering a change of plan for the insurer.
By Cathy Wilks and Matt Gosnell
Data visualisation is effective when we can trust the data we’re looking at. It has to be easily understood, and it has to be easy to read and decipher. It enables businesses to make quicker decisions and helps them to communicate with others in a relatable way.
By Robert Guidi
Picture the scene: the movie executives, producers and the director sit as the audience in a horse-shoe. At the centre, a humanoid robot “pitches” an idea for a feature film. Within seconds one of the producers rejects it as “too fluffy” and the others agree. Rejected. The robot thinks again, and produces another plot on the spot, modified to take the feedback into account. By the end of the one hour meeting, the director has three new scripts in development; the Artificial Intelligence (AI) engine driving the robot has already produced the 120 page drafts.
By Adrian Hughes
Many people talk about Management Information (MI) as if it’s a standard, uniform product. What’s easy to forget is that one organisation’s MI looks very different from another’s, even if they’re in the same sector. It’s rather like comparing hairstyles – it’s subtly different for each of us and how we choose to cut, colour and style it is uniquely personal (although I can only dream of those days sadly…).
By Phil Mennie
Data is everywhere. And social media is just one of the ways we’re creating massive sets of data every day, every minute, every second. From posting a status to clicking ‘like’ – just how much are we sharing about our lives on Facebook? And how much do we want companies to know about us?
By Michel Abbink
Financial Services organisations make predictions all the time, in all parts of their business. Guessing what the future might hold and aligning decisions with these estimates, is implicitly what most organisations do.
Organisations often take ad-hoc approaches to such predictions, leaving experts and professionals free to apply their judgement. Research has shown that this can lead to a hidden cost of inconsistent and sometimes suboptimal decision making.
By Nigel Wilson
Since Icarus and his dad looked at the birds in the sky to inspire their escape from Crete, humans have attempted to mimic the natural world. Two thousand years later, we have engineered ways to swim, fly and travel faster than nature, but are we finally ready to build a machine that can think faster than anything in nature?
By Adrian Hughes
Britain and America, the saying goes, are two countries divided by a common language. There have been numerous occasions during my working life in data analytics when a similar thought has crossed my mind. We have extraordinary power to collect, collate and analyse data and yet we often fail to ask ourselves the most basic of questions: Does this word mean the same thing to everyone?
By Checca Aird
Historically the public sector has been lightyears behind the private sector when it comes to utilising technology in their operations, and even later to the party when recognising the value of the data they hold, however recent developments encouraging government transparency and efficiency have forced officials to rethink the issue.
Big Data is one of The Government’s Eight Great Technologies to support UK science strengths and business capabilities, but research such as PwC’s Global Data & Analytics Survey
By Paul Delbridge In my first London Market focused blog, "How London Market insurers are responding to the perfect storm of challenges", I touched on the competitive advantages that could rise from exploiting Data Analytics. I believe that predictive analytics is key to boosting underwriting returns in the London Market...
By Sudheer Parwana
“Regulatory Compliance” is a phrase which my clients very rarely say with warm fuzzy feelings and cheerful thoughts. And why would they? In recent years there has been a greater focus on ensuring organisations operate legally, safely and ethically as a result of new social trends, technology advancements and greater globalisation. To make this happen, new regulations are increasingly being imposed at a rapid pace and I suspect June’s vote on Brexit will only add further complexity once it is in full flow.
By Richard Petley
I’ve worked in data governance for 15 years and I can safely say that this is the most interesting time that I’ve experienced – and that’s partly because no two people in the world have the same view about what data governance means.
Ask a company that has recently suffered a data breach and they’ll tell you that data governance is all about preventing a data leak and avoiding the wrath of the Information Commissioner
By Mark Schofield
The tax function is one of the largest consumers of data in organisations. Typically, according to a joint study we carried out with the Manufacturers Alliance for Productivity and Innovation (MAPI) tax spends more than half of its time gathering data. It’s something that tax functions excel at even though this is becoming more challenging as tax data is housed in many locations and the volume of data is increasing