Are Master Data Management and Hadoop a Good Match?

Master Data is the critical electronic information about the company we cannot afford to lose. Accordingly, we should sanitise it, look after it, and store it safely in several separate places that are independent of each other. The advent of Big Data introduced the current era of huge repositories ?in the clouds?. They are not, of course but at least they are remote. This short article includes a discussion about Hadoop, and whether this is a good platform to back up your Master Data.

About Hadoop

Hadoop is an open-source Apache software framework built on the assumption that hardware failure is so common that backups are unavoidable. It comprises a storage area and a management part that distributes the data to smaller nodes where it processes faster and more efficiently. Prominent users include Yahoo! and Facebook. In fact more than half Fortune 50 companies were using Hadoop in 2013.

Hadoop – initially launched in December 2011 ? has survived its baptism of fire and became a respected, reliable option. But is this something the average business owner can tackle on their own? Bear in mind that open source software generally comes with little implementation support from the vendor.

The Hadoop Strong Suite

  • Free to download, use and contribute to
  • Everything you need ?in the box? to get started
  • Distributed across multiple fire-walled computers
  • Fast processing of data held in efficient cluster nodes
  • Massive scaleable storage you are unlikely to run out of

Practical Constraints

There is more to Hadoop than writing to WordPress. The most straightforward solutions are uploading using Java commands, obtaining an interface mechanism, or using third party vendor connectors such as ACCESS or SAS. The system does not replace the need for IT support, although it is cheap and exceptionally powerful.

The Not-Free Safer Option

Smaller companies without in-depth in-house support are wise to engage with a technical intermediary. There are companies providing commercial implementations followed by support. Microsoft, Amazon and Google among others all have commercial versions in their catalogues, and support teams at the end of the line.

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FUJIFILM Cracks the Energy Code

FUJIFILM was in trouble at its Dayton, Tennessee plant in 2008 where it produced a variety of speciality chemicals for industrial use. Compressed-air breakdowns were having knock-on effects. The company decided it was time to measure what was happening and solve the problem. It hoped to improve reliability, cut down maintenance, and eliminate relying on nitrogen for back-up (unless the materials were flammable).

The company tentatively identified three root causes. These were (a) insufficient system knowledge within maintenance, (b) weak spare part supply chain, and (c) generic imbalances including overstated demand and underutilised supply. The maintenance manager asked the U.S. Department of Energy to assist with a comprehensive audit of the compressed air system.

The team began on the demand side by attaching flow meters to each of several compressors for five days. They noticed that – while the equipment was set to deliver 120 psi actual delivery was 75% of this or less. They found that demand was cyclical depending on the production phase. Most importantly, they determined that only one compressor would be necessary once they eliminated the leaks in the system and upgraded short-term storage capacity.

The project team formulated a three-stage plan. Their first step would be to increase storage capacity to accommodate peak demand; the second would be to fix the leaks, and the third to source a larger compressor and associated gear from a sister plant the parent company was phasing out. Viewed overall, this provided four specific goals.

  • Improve reliability with greater redundancy
  • Bring down system maintenance costs
  • Cut down plant energy consumption
  • Eliminate nitrogen as a fall-back resource

They reconfigured the equipment in terms of lowest practical maintenance cost, and moved the redundant compressors to stations where they could easily couple as back-ups. Then they implemented an online leak detection and repair program. Finally, they set the replacement compressor to 98 psi, after they determined this delivered the optimum balance between productivity and operating cost.

Since 2008, FUJIFILM has saved 1.2 million kilowatt hours of energy while virtually eliminating compressor system breakdowns. The single compressor is operating at relatively low pressure with attendant benefits to other equipment. It is worth noting that the key to the door was measuring compressed air flow at various points in the system.

ecoVaro specialises in analysing data like this on any energy type.?

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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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