GDPR

5 things to consider when selecting your next online storage provider

As the demand for managed cloud and professional services rises, the considerations behind choosing the right cloud storage partner becomes more pertinent. There is a large range of variables that affect these providers’ ability to keep your data secure, your connectivity robust, and your costs low.Most data centres were “state-of-the-art” when they were built, yet…


As the demand for managed cloud and professional services rises, the considerations behind choosing the right cloud storage partner becomes more pertinent. There is a large range of variables that affect these providers’ ability to keep your data secure, your connectivity robust, and your costs low.

Most data centres were “state-of-the-art” when they were built, yet infrastructure quickly becomes obsolete if it does not adapt to the constant changes in regulation, cyber threats, and users’ needs and expectations.

Choosing the wrong cloud storage provider can have significant consequence on a business’s operations, including factors such as performance and business continuity problems, security vulnerabilities, and costs.

It pays to do due diligence before beginning a relationship of such strategic importance, so here are the five most important questions you should ask when choosing a cloud storage provider.

  • Best ways to transfer files online in 2019
  • Best ways to share big files
  • Best ways to share files securely

1. Location, location, location

In today’s hyper-connected world, it may not seem important if your data is located across town or on the other side of the world. In fact, it’s crucial to know exactly where your precious data will reside. This is important not just from a legal point of view (with legislation such as GDPR governing where some data resides) but also for a range of business continuity and performance factors.

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GDPR

How to fix the broken sales funnel

Business agility and the ability to respond fast to new sales opportunities has never been more important and a strong, intelligence-led sales model is essential to maximise opportunities. Yet in this post GDPR era, sales models have never been weaker or less efficient. A lack of data confidence is undermining outbound activity, leaving companies reliant…


Business agility and the ability to respond fast to new sales opportunities has never been more important and a strong, intelligence-led sales model is essential to maximise opportunities. Yet in this post GDPR era, sales models have never been weaker or less efficient. A lack of data confidence is undermining outbound activity, leaving companies reliant on increasingly expensive inbound campaigns that are not delivering.

To fix the broken sales funnel, organisations clearly need to use to fresh, accurate and GDPR compliant data. But that is just the start: successful sales activity is underpinned by a scientific, structured and metrics driven approach that leverages multi-dimensional real-time data.

  • Ensure data integrity by turning CRM usage into a game
  • Choosing the right data security solution for big data environments
  • Building reliable data pipelines with AI and DataOps

Science not art

Fewer good prospects. Delayed decision making. Ever lengthening sales cycles. A lack of predictability in the sales process. For many companies, the sales funnel is looking less than impressive. Yet while the temptation is to blame new restrictions of data privacy created by GDPR on the other, there is little value in playing the blame game. What companies require is a solution.

Where is the sales funnel broken and how can it be fixed? Understanding the ‘where’ is key – and something that far too many companies fail to address. How many good sales-people have been fired, when the problem was poor data? How much time has been wasted on prioritising the wrong prospects or failing to correctly identify the total addressable market?

A broken sales funnel cannot be repaired just by adding technology, replacing sal

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GDPR

What’s been done for data privacy since GDPR?

This year, privacy continues to be the most important aspect of data management as an increasing number of consumers are growing concerned about their privacy and the security of their personal information. According to research from the Global Web Index, 51% of European respondents are concerned about the Internet eroding their personal privacy and 60% worry…


This year, privacy continues to be the most important aspect of data management as an increasing number of consumers are growing concerned about their privacy and the security of their personal information. 

According to research from the Global Web Index, 51% of European respondents are concerned about the Internet eroding their personal privacy and 60% worry about how their personal information is being used by companies. In the US, these figures rise to 62% and 65% respectively. While in Europe GDPR was introduced to protect consumers’ privacy and safeguard their data, it also seems to have increased awareness of the misuse of data. People now realise the importance and value of their personal information and, as a result, are demanding greater control over their information and increasingly becoming unwilling to give up that information.

While organisations already put processes in place to drive compliance with GDPR, those organisations must recognise and acknowledge this consumer trend and continue to enhance their processes and policies to sustain a data privacy program and ensure the proper protections and safeguards. Failing to do so could result in dire consequences, not only in terms of fines from regulatory agencies, but also failing to protect privacy and safeguard personal information, even slightly, could cost them the trust of their customers. 

  • Why data privacy without data visibility doesn’t cut it for GDPR
  • Ten tips for GDPR compliance
  • GDPR Subject Access Request: authentication cannot be an afterthought

Additionally, as companies come to grips with the privacy and security issues relating to personal information, the concept of information ethics is coming to the fore. So, what are businesses doing in order to provide for continuous improvement around the issue of privacy? And what does information ethics mean for data privacy?

Image credit: Shutterstock 

Image credit: Shutterstock 

(Image: © Wright Studio / Shutterstock)

Creating new roles

As businesses start to understand the idea of information ethics being a major corollary to data privacy and security, more and more organisations begin to look not only at what they could do with data but what they should do with data. And this should is not from the perspect

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GDPR

The unintended consequences of emerging compliance regulations

Online data is more prevalent and valuable than ever before, for consumers, businesses and fraudsters alike. While the ability to do anything, from anywhere has its benefits, including convenience and constant connectivity, there’s also a dark side: criminals waiting to exploit your most personal, sensitive information. In fact, the total number of personal records exposed…


Online data is more prevalent and valuable than ever before, for consumers, businesses and fraudsters alike. While the ability to do anything, from anywhere has its benefits, including convenience and constant connectivity, there’s also a dark side: criminals waiting to exploit your most personal, sensitive information. In fact, the total number of personal records exposed in data breaches more than doubled over 2018, compared to 2017. 

The value of data has led to new legislation intended to protect information shared and stored online. Europe’s GDPR became binding in May 2018, and a variant in California is slated to become effective in 2020, complicating matters for companies that limited their European data presence in hopes of avoiding GDPR. In addition, the revised Payment Services Directive (PSD2), intended to democratize access to data and simultaneously protect it through Strong Customer Authentication (SCA), will come into effect in Europe in September 2019.

  • Why it’s high time we regulated Big Tech
  • The GDPR paradox: how data regulation creates revenue streams
  • Google fined €50m by French data regulator

A closer look at the unintended consequences

Perversely, both GDPR and PSD2, which were created to protect customers and their data, actually introduce new risks and complications for businesses operating online.

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GDPR

AI’s memory is perfect for insight into collective behaviour

AI was never intended to give insights into collective behaviour, yet it’s becoming an increasingly efficient method of doing so. In an age of the GDPR fearful, collective behaviour is the way forward to understanding consumer preferences and AI’s memory of data allows this to happen without jeopardising individual behaviour. Three ways CIOs can successfully scale AITrump…


AI was never intended to give insights into collective behaviour, yet it’s becoming an increasingly efficient method of doing so. 

In an age of the GDPR fearful, collective behaviour is the way forward to understanding consumer preferences and AI’s memory of data allows this to happen without jeopardising individual behaviour. 

  • Three ways CIOs can successfully scale AI
  • Trump administration orders research into AI
  • Three quarters of smartphones will have AI chip by 2022

Early beginnings

Alan Turing was recently named as the most ‘iconic’ figure of the 20th century. Perhaps this is because of the explosive interest and power that artificial intelligence is set to have on our world in the near future. 

He was a mathematician who cracked codes during World War II and praised with shortening the war by several years due to his work at Bletchley Park. Here, he was tasked with cracking the ‘Enigma’ code and, with another code-breaker, invented a machine known as the Bombe which has had a huge influence on the development of computer science and artificial intelligence.

Turing suggested that humans use available information as well as reason in order to solve problems and make decisions, so machines should, in theory, be able to do the same. This was the logical framework of his 1950 paper, Computing Machinery and Intelligence, in which he discusses how to build intelligent machines and how to test their intelligence.

After a conference in 1956 where, what is considered by many, to be the first AI programme was presented, a flurry of interest in AI ensued. Computers could store more information and became faster, cheaper, and more accessible. Machine learning algorithms improved and people got better at knowing which algorithm to apply to their problem. However, a mountain of

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