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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EcoVaro ? ESOS Solution on a Cloud

The UK?s Energy Saving Opportunity Scheme ? and all others in the EU stable – is bound to generate huge quantities of data beyond the reach of processing on standalone computers. This leaves some companies in the mandatory sector between a rock and a hard place. They already have to divert scarce talent to draft compliance reports. Now they face purchasing equipment with big data processing power.

The more astute are turning to cloud computing solutions like EcoVaro in increasing numbers. They are also keen to benefit from remote secure backup. .

Increasing migration to public clouds has caused a growth in niche big data consultants. EcoVaro is one of these. We want to do more than simply open up a port and leave you to become familiar with our technology. We service a growing group of companies who want us to analyse their energy usage reports, and isolate the main demand drivers so they know where to start saving.

We are consumer-centric energy consultants with the emphasis on corporates and sme?s. We offer more than just big data processing facilities. We also help set up your dashboard and are full of practical ideas you can use to start trimming energy costs right away. So please treat us as your affordable energy partner who really wants to help.

Finally, contact EcoVaro for a discussion.

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Technology and process improvement

Tightening organisational flow to improve productivity and minimise costs is a growing concern for many businesses post the Global Financial Crisis. Businesses can no longer afford to waste time and personnel on inefficient processes. Organisations using either Six Sigma or Lean techniques better manage their existing resources to maximise product out-put. Both of these techniques involve considerable evaluation of current processes.

What is Six Sigma?

Six Sigma is an organisational management strategy that evaluates processes for variation. In the Six Sigma model, variation equates waste. Eliminating variation for customer fulfilment allows a business to better serve the end-user. In this thought model, the only way to streamline processes is to use statistical data. Each part of a process must be carefully recorded and analysed for variation and potential improvements. The heart of the strategy embodied by Six Sigma is mathematical. Every process is subject to mathematical analysis and this allows for the most effective problem solving.

What is a Lean Model?

Lean businesses do not rely on mathematical models for improvement. Instead, the focus is on reducing steps in the customer delivery cycle, which do not add value to the final deliverable. For example, maintaining excess inventory or dealing with shortages would both be examples of waste behaviour. Businesses that operate using Lean strategies have strong cash flow cycles. One of the best and most famous examples of Lean in action is the Toyota Production System (TPS). In this system, not only is inventory minimised, but physical movement for employees also remains sharply controlled. Employees are able to reach everything needed to accomplish their tasks, without leaving the immediate area. By reducing the amount of movement needed to work, companies also remove wasted employee time.

Industry Applications for Lean and Six Sigma

Lean businesses reduce the number of steps between order and delivery. The less inventory on hand, the less it costs a business to operate. In industries where it is possible to create to order, Lean thinking offers significant advantages. Lean is best utilised in mature businesses. New companies, operating on a youthful model, may not be able to identify wasteful processes. Six Sigma has shown its value across industries through several evolution’s. Its focus on quality of process makes it a good choice for even brand new businesses. The best use is the combination of the two strategies. With the Lean focus on speed and the Six Sigma focus on quality combined, the two organisational processes create synergy. By itself, Lean does not help create stable, repeating success. Six Sigma does not help increase speed and reduce non value-added behaviours. Combined, these two strategies offer incredible value to every business in cost savings.

Using Technology to Implement Lean Six Sigma

Automation processes represent an opportunity for businesses to implement a combination of both Lean and Six Sigma strategies. Any technology that replaces the need for direct human oversight reduces costs and increases productivity. A few examples of potentially cost saving IT solutions include document scanning, the Internet, and automated workflow systems.

  • Document Scanning – Reducing dependency on paper copies follows both Lean and Six Sigma strategies. It is a Lean addition in that it allows employees to access documents instantly from any physical location. It is Six Sigma compliant in that it allows a reduction on process variation, since there is no bottleneck on the flow of information.
  • The Internet – The automation potential offered by the Internet is limitless. Now, businesses can enter orders, manage logistics and perform customer service activities from anywhere, through a hosted portal. With instant access to corporate processes from anywhere, businesses can manage workflow globally, allowing them to realise cost savings from decentralisation.
  • Automated Work Systems – One of the identified areas of waste in any business is processing time. The faster orders are processed and delivered, the greater the profits for the company and the less the expense per order. When orders sit waiting for attention, they represent lost productivity and waste. Automated work systems monitor workflow and alert users when an item sits longer than normal. These systems can also reroute work to an available employee when the original worker is tied up.

Each of these IT solutions provides a method for businesses to either reduce the number of steps in a process or improve the quality of the process for improved customer service.

Identifying Areas for Lean Six Sigma Implementation

Knowing that improved processes result in improved profits, identifying areas for improvement is the next step. There are several techniques for creating tighter processes with less waste and higher quality. Value Stream Mapping helps business owners and managers identify areas of waste by providing a visual representation of the total process stream. Instead of improving single areas for minimal increases in productivity, VSM shows the entire business structure and flow, allowing management to target each area of slow down for maximum improvement in all areas.

Seeing the areas of waste helps management better determine how processes should work to best obtain the desired outcomes. Adding in automated processes helps with improved process management, when put in place with a complete understanding of current systems and their weaknesses. Start with mapping and gain a bird’s-eye view of the situation, in order to make the changes needed for improvement.

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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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