The General Data Protection Regulation & The Duty to use Encryption

The General Data Protection Regulation, abbreviated to GDPR, raised a storm when it arrived. In reality, it merely tightened up on existing good practice according to digital security specialists Gemalto. The right to withhold consent and to be forgotten has always been there, for example. However, the GDPR brings a free enforcement service for consumers, thus avoiding the need for third party, paid assistance.

The GDPR Bottom Lines for Data Security
Moreover, the GDPR has penalties it can apply, of the order that might have a judge choking on his wig. Under it, data security measures such as pseudonymisation (substitution of identifying fields) and encryption (encoding including password protection) have become mandatory. Businesses must further respect their client data by:

a) Storing it in a secure environment supported by robust services and systems

b) Having proven measures to restore availability and access after a breach

c) Being able to prove frequent effectiveness testing of these measures.

The General Data Protection Regulation places an onus on businesses to report any data breaches. This places us in a difficult situation. We must either face at least a wrist slap upon reporting failures. Alternatively, pay a fine of up to ?10 million, or 2% of total worldwide annual turnover.

The Engineered Weak Link in the System
Our greatest threat of breach is probably when the data leaves our secure environment, and travels across cyberspace to an employee, stakeholder, collaborator, or the client themselves. Since email became open to attack, businesses and individuals have turned to sharing platforms like Dropbox, Google Drive, Skydrive, and so on. While these do allow an additional layer of password protection, none of these has proved foolproof. The GDPR may still fine us heavily, whether or not we are to blame for the actual breach.

How Hacking is Approaching Being a Science
We may make a mistake we may regret, if we do not take hacking seriously. The 10 worst data hacks Identity Force lists are proof positive that spending lots of money does not guarantee security (any more than having the biggest stock of nuclear weapons). We have to be smart, and start thinking the way that hackers do.

Hacker heaven is finding an Experian or a Dun & Bradstreet that may have shielded 143 million, and 33 million consumer records respectively, behind a single, flimsy cyber-security door. Ignorance is no excuse for them. They should simply have known better. They should have rendered consumer data unreadable at individual record level. The hackers could have found this too demanding to unpick, and have looked elsewhere.

How Data Encryption Can Help Prevent Hackers Succeeding
Encrypting data is dashboard driven, and businesses need not concern themselves about it works. There are, however, a few basic decisions they must take:

a) Purge the database of all information held without explicit permission

b) Challenge the need for the remaining data and purge the nice-to-haves

c) Adopt a policy of encrypting access at business and customer interfaces

d) Register with three freemium encryption services that seem acceptable

e) After experimenting, sign up for a premium service and be prepared to pay

Factors to Consider When Reaching a Decision
Life Hacker?suggests the following criteria although the list is a one-size-fits-all

a) Is the system fast, simple, and easy to operate

b) Can you encrypt hidden volumes within volumes

c) Can you mass-encrypt a batch of files easily

d) Do all other files remain encrypted when you open one

e) Do files automatically re-encrypt when you close them

f) How confident are you with the vendor, on a scale of 1 to 10

It may be wise to encrypt all the files on your system, and not just your customer data. We are always open to a hack by the competition after our strategic planning. If we leave the decision up to IT, then IT, being human may take the easy way out, and encrypt as little as possible.

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Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

Keys to Successful Matrix Management

Matrix management, in itself, is a breakthrough concept. In fact, there are a lot of organizations today that became successful when they implemented this management technique. However, there are also organizations that started it but failed. And eventually abandoned it in the end.

Looking at these scenarios, we can say that when you implement matrix management in your organisation, two things can happen – you either succeed or fail. And there?s nothing in between. The truth is, the effectiveness of matrix management lies in your hands and in your implementation. To ensure that you achieve your desired results, recognise these essential keys to successful matrix management.

Establish Performance Goals and Metrics

This should be done as soon as the team is formed, at the beginning of the year or during the process of setting organisational objectives. Whenever it is, the most important thing is that each team player understands the objectives and metrics to which their performances will be evaluated. This ensures that everyone is looking at the same set of objectives as they carry out their individual tasks.

Define Roles and Responsibilities

One pitfall of matrix management is its internal complexity. Awareness of this limitation teaches you to clearly define the roles and responsibilities of the team players up front. Basically, there are three principal sets of roles that should be explained vividly ? the matrix leader, matrix managers and the matrixed employees. It is important to discuss all the possible details on these roles, as well as their specific responsibilities, to keep track of each other?s participation in the projects of the organisation.

One effective tool to facilitate this discussion is through the RACI chart – Who is Responsible? Who is Accountable? Who should be Consulted? Who will Implement? With this, clarification of roles and responsibilities would be more efficient.

When roles are already clearly defined, each participant should review their job descriptions and key performance metrics. This is to make sure that the roles and responsibilities expected of you integrates consistently with your job in the organisation, as a whole.

Manage Deadlines

In matrix management, the employees report to several managers. They will likely have multiple deadlines to attend to and accomplish. There might even be conflicts from one deadline to another. Hence, each should learn how to schedule and prioritise their tasks. Time management and action programs should be incorporated to keep the grace under pressure.

Deliver Clear Communication

Another pitfall of matrix management is heightened conflict. To avoid unrealistic expectations, the matrix leaders and managers should communicate decisions and information clearly to their subordinates, vice versa. It would help if everyone will find time to meet regularly or send timely reports on progress.

Empower Diversity

Knowledge, working styles, opinions, skills and talents are diverse in a matrix organisation. Knowing this fact, each should understand, appreciate and empower the learning opportunities that this diversity presents. Trust is important. Respect to each other?s opinions is vital. And acknowledgement of differing viewpoints is crucial.

The impetus of matrix management is the same ? mobilise the organisation’s resources and skills to cope with the fast-paced changes in the environment. So, maximise the benefits of matrix management as you consider these essential keys to its successful implementation.

Directions Hadoop is Moving In

Hadoop is a data system so big it is like a virtual jumbo where your PC is a flea. One of the developers named it after his kid?s toy elephant so there is no complicated acronym to stumble over. The system is actually conceptually simple. It has loads of storage capacity and an unusual way of processing data. It does not wait for big files to report in to its software. Instead, it takes the processing system to the data.

The next question is what to do with Hadoop. Perhaps the question would be better expressed as, what can we do with a wonderful opportunity that we could not do before. Certainly, Hadoop is not for storing videos when your laptop starts complaining. The interfaces are clumsy and Hadoop belongs in the realm of large organisations that have the money. Here are two examples to illustrate the point.

Hadoop in Healthcare

In the U.S., healthcare generates more than 150 gigabytes of data annually. Within this data there are important clues that online training provider DeZyre believes could lead to these solutions:

  • Personalised cancer treatments that relate to how individual genomes cause the disease to mutate uniquely
  • Intelligent online analysis of life signs (blood pressure, heart beat, breathing) in remote children?s hospitals treating multiple victims of catastrophes
  • Mining of patient information from health records, financial status and payroll data to understand how these variables impact on patient health
  • Understanding trends in healthcare claims to empower hospitals and health insurers to increase their competitive advantages.
  • New ways to prevent health insurance fraud by correlating it with claims histories, attorney costs and call centre notes.

Hadoop in Retail

The retail industry also generates a vast amount of data, due to consumer volumes and multiple touch points in the delivery funnel. Skillspeed business trainers report the following emerging trends:

  • Tracing individual consumers along the marketing trail to determine individual patterns for different demographics and understand consumers better.
  • Obtaining access to aggregated consumer feedback regarding advertising campaigns, product launches, competitor tactics and so on.
  • Staying with individual consumers as they move through retail outlets and personalising their experience by delivering contextual messages.
  • Understanding the routes that virtual shoppers follow, and adding handy popups with useful hints and tips to encourage them on.
  • Detecting trends in consumer preferences in order to forecast next season sales and stock up or down accordingly.

Where to From Here?

Big data mining is akin to deep space research in that we are exploring fresh frontiers and discovering new worlds of information. The future is as broad as our imagination.?

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