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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Is the GDPR Good or Bad News for Business

The European Union?s General Data Protection Act (GDPR) is a new data authority coming into force on 25 May 2018. It replaces the current Data Protection Directive 95/46/EC, while extending the remit to include the export of personal data outside the EU. It aims to give EU citizens and residents living there more control over their personal information. It also hopes to make regulatory compliance simpler for participating businesses.

The Broad Implications for Business
The GDPR puts another layer of accountability on businesses falling within its remit. It requires them to implement ?comprehensive but proportionate governance measures? including recording how they make decisions. The long-term goal is to reduce privacy infringements. In the short run, businesses without good governance may find themselves writing new policies and procedures.

Article 5 of the European Union?s General Data Protection Act lays down the following guidelines for managing personal data. This shall be ?
? Processed transparently, fairly, and lawfully
? Acquired for specific, legitimate purposes only
? Adequate, relevant and limited to essentials
? Not used for any other, incompatible purpose
? However it may be archived in the public interest
? Kept up to date with all inaccuracies corrected
? Ring-fenced when the information becomes irrelevant
? Adequately protected against unauthorised access
? Stored in a way that prevents accidental loss
Furthermore, affected businesses shall appoint a ?controller responsible for, and able to demonstrate, compliance with the principles.?

Implementing Accountability and Governance
The UK Information Commissioner?s Office has issued guidelines regarding provisions to assure governance and accountability. These are along the lines of the ?don’t tell me, show me? management approach the office has generally been following. In summary form, a business, and its controller must:
? Implement measures that assist it to ensure demonstrated compliance
? Maintain suitable, relevant records of personal data processing activities
? Appoint a dedicated data protection officer if scale makes this appropriate
? Implement technologies that ensure data protection by design
? Conduct data protection assessments and respond to results timeously

Implementing the General Data Protection Act in Ireland
The Irish Data Protection Commissioner has decided it is unnecessary to incorporate the GDPR into Irish law, since EU regulations have direct effect. The office of the Commissioner is working in tandem with data practitioners, and industry and professional bodies to raise awareness in business through 2017. It has produced a document detailing what it considers the essentials for business compliance. Briefly, these pre-requisites are:
? Ensure awareness among key personnel, and make sure they incorporate the GDPR into their planning
? Conduct an early assessment of quality management gaps, and budget for additional resources needed
? Do an audit of personal data held, to determine the origin, the necessity to hold it, and with whom shared
? Inform internal and external stakeholders of the current status, and your future plans to implement the GDPR
? Examine current procedures in the light of the new directive. Could you ?survive? a challenge from a data subject?
? Determine how you will process requests for access to the data in the future from within and outside your organization
? Assess how you currently obtain customer consent to store their data. Is this “freely given, specific, informed and unambiguous”?
? Find how you handle information from underage people. Do you have systems to verify ages and obtain guardian consent?
? Implement procedures to detect, investigate, and report data breaches to the Data Protection Commissioner within 72 hours
? Implement a culture of always assessing the effect on individual privacy before starting new initiatives

So Is the GDPR Good or Bad for Business
The GDPR should be good news for business customers. Their personal data will be more secure, and they should see their rate of spam marketing come down. The GDPR is also good news for businesses currently investing resources to protect their clients? interests. It could however, be bad news for businesses that have not been focussing on these matters. They may have a high mountain to climb to come in line with the GDPR.
Disclaimer: This article is for information only and not intended as a comprehensive guide.

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Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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UK Government Updates ESOS Guidelines

Britain?s Environment Agency has produced an update to the ESOS guidelines previously published by the Department of Energy and Climate Change. Fortunately for businesses much of it has remained the same. Hence it is only necessary to highlight the changes here.

  1. Participants in joint ventures without a clear majority must assess themselves individually against criteria for participation, and run their own ESOS programs if they comply.
  2. If a party supplying energy to assets held in trust qualifies for ESOS then these assets must be included in its program.
  3. Total energy consumption applies only to assets held on both the 31 December 2014 and 5 December 2015 peg points. This is relevant to the construction industry where sites may exchange hands between the two dates. The definition of ?held? includes borrowed, leased, rented and used.
  4. Energy consumption while travelling by plane or ship is only relevant if either (or both) start and end-points are in the UK. Foreign travel may be voluntarily included at company discretion. The guidelines are silent regarding double counting when travelling to fellow EU states.
  5. The choice of sites to sample is at the discretion of the company and lead assessor. The findings of these audits must be applied across the board, and ?robust explanations? provided in the evidence pack for selection of specific sites. This is a departure from traditional emphasis on random.

The Environment Agency has provided the following checklist of what to keep in the evidence pack

  1. Contact details of participating and responsible undertakings
  2. Details of directors or equivalents who reviewed the assessment
  3. Written confirmation of this by these persons
  4. Contact details of lead assessor and the register they appear on
  5. Written confirmation by the assessor they signed the ESOS off
  6. Calculation of total energy consumption
  7. List of identified areas of significant consumption
  8. Details of audits and methodologies used
  9. Details of energy saving opportunities identified
  10. Details of methods used to address these opportunities / certificates
  11. Contracts covering aggregation or release of group members
  12. If less than twelve months of data used why this was so
  13. Justification for using this lesser time frame
  14. Reasons for including unverifiable data in assessments
  15. Methodology used for arriving at estimates applied
  16. If applicable, why the lead assessor overlooked a consumption profile

Check out: Ecovaro ? energy data analytics specialist 

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