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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The Future of Cloud Backup and Recovery

We came across a post on Docurated that pulled together thirty-seven suggestions for the top cloud storage mistakes user companies make. Given that cloud storage seems to be the best backup solution for now at least, we decided to turn these ideas around to sense the direction cloud backup and recovery needs to take, if it is still to be relevant in say ten years? time.

Has Cloud Storage Largely Saturated the West?
It probably has. Outside of major corporates who make their own arrangements ? and SME?s that use free services by email providers ? the middle band of companies in Europe and America have found their service providers, although they may have never tested the recovery process, to see if it works.

The new gold rush in the cloud backup and recovery business is, or should be emerging markets in Asia, Africa, South America, and the Middle East. There, connectivity is brittler than over here. To be relevant in these fragile, more populous areas our cloud backup and recovery industry need to be more agile and nimble.

? It must provide a simpler service emerging commerce can afford, refresh its user interfaces in third world languages, have more accessible help, and be patient to explain how cloud storage works to newbies. In other words, it must source its call centre operators in the areas it serves.

? It must adapt to local connectivity standards, and stop expecting someone with ADSL broadband to keep up with cloud server networks running at up to 1GBPS compared to their 10MBPS at best. For user sourcing and retention purposes, these new cloud backup and recovery services must be the ones who adapt.

? It must facilitate disaster recovery simulations among its clients in calmer moments when things are going well. Are they backing up the right files, are they updating these, and are their brittle ADSL networks able to cope with their cloud service providers? upload and download speeds?

? It must develop lean and agile systems slim enough to accommodate a micro client starting out, but sufficiently elastic to transfer them seamlessly to big data performance. The Asian, African, South American, and Middle Eastern regions are volume driven, and individual economies of scale are still rare.

? It must not expect its users to know automatically what they need, and be honest to admit that Western solutions may be wrong-sized. Conversion funnels in the new gold rush are bound to be longer. Engagements there depend on trust, not elevator sales letters. Our competition in these countries already works this way.

? It must be honest and admit cloud storage is only part of the solution. To recruit and retain users it must step back to 1983, when Compuserve offered its customers 128k of disc space, and spent an amount of effort explaining how to filter what to put there.

Cloud Storage of Data is Only One Part of the Solution
Governance reports and stock certificates burn just as easily as do servers in a fire. We must not transfer bad habits to exciting new markets. We close this article with the thoughts of John Howie, COO of Cloud Security Alliance, as reported in the Docurated post we mentioned, and these apply across the globe, we believe.
There is no single most important thing to carry forward into the future of cloud backup and recovery. We must be mindful when moving data that this can be fragile too. We must also create layers of backup the way insurance companies re-insure, that make any one cloud backup and recovery business redundant if it happens.
We hold the trust of our customers in our hands but trust is delicate too. We must cease trying to make a pile of money quickly, and become more interested in ensuring that data transferred back and forth is synchronised. The cloud backup and recovery industry needs only one notorious mistake, to become redundant itself in the ten years we mentioned.

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What Kanban can do for Call Centre Response Times

When a Toyota industrial engineer named Taiichi Ohno was investigating ways to optimise production material stocks in 1953, it struck him that supermarkets already had the key. Their customers purchased food and groceries on a just-in-time basis, because they trusted continuity of supply. This enabled stores to predict demand, and ensure their suppliers kept the shelves full.

The Kanban system that Taiichi Ohno implemented included a labelling system. His Kanban tickets recorded details of the factory order, the delivery destination, and the process intended for the materials. Since then, Ohno?s system has helped in many other applications, especially where customer demand may be unpredictable.

Optimising Workflow in Call Centres
Optimising workflow in call centres involves aiming to have an agent pick up an incoming call within a few rings and deal with it effectively. Were this to be the case we would truly have a just-in-time business, in which operators arrived and left their stations according to customer demand. For this to be possible, we would need to standardise performance across the call centre team. Moving optimistically in that direction we would should do these three things:

  • Make our call centre operation nimble
  • Reduce the average time to handle calls
  • Decide an average time to answer callers

When we have done that, we are in a position to apply these norms to fluctuating call frequencies, and introduce ?kanbanned? call centre operators.

Making Call Centre Operations Nimble
The best place to start is to ask the operators and support staff what they think. Back in the 1960?s Robert Townsend of Avis Cars famously said, ?ask the people ? they know where the wheels are squeaking? and that is as true as ever.

  1. Begin by asking technical support about downtime frequencies, duration, and causes. Given the cost of labour and frustrated callers, we should have the fastest and most reliable telecoms and computer equipment we can find.
  1. Then invest in training and retraining operators, and making sure the pop-up screens are valuable, valid, and useful. They cannot do their job without this information, and it must be at least as tech-savvy as their average callers are.
  1. Finally, spruce up the call centre with more than a lick of paint to awaken a sense of enthusiasm and pride. Find time for occasional team builds and fun during breaks. Tele-operators have a difficult job. Make theirs fun!

Reducing Average Time to Handle Calls
Average length of contact is probably our most important metric. We should beware of shortening this at the cost of quality of interaction. To calculate it, use this formula:

Total Work Time + Total Hold Time + Total Post Call Time

Divided By

Total Calls Handled in that Period

Share recordings of great calls that highlight how your best operators work. Encourage role-play during training sessions so people learn by doing. Publish your average call-handling time statistics. Encourage individual operators to track how they are doing against these numbers. Make sure your customer information is up to date. While they must confirm core data, limit this so your operators can get down to their job sooner.

Decide a Target Time to Answer Calls
You should know what is possible in a matter of a few weeks. Do not attempt to go too tight on this one. It is better to build in say 10% slack that you can always trim in future. Once you have decided this, you can implement your Kanban system.

Introducing Kanban in Your Call Centre Operation
Monitor your rate of incoming calls through your contact centre, and adjust your operator-demand metric on an ongoing basis. Use this to calculate your over / under demand factor. Every operator should know the value on this Kanban ticket. It will tell them whether to speed up a little, or slow down a bit so they deliver the effort the call rate demands. It will also advise the supervisor when to call up reserves.

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Big Energy Data Management

Recent times have seen the advent of cloud based services and solutions where energy data is being stored in the cloud and being accessed from anywhere, anytime through remote mobile devices. This has been made possible by web-based systems that can usually bring real-time meter-data into clear view allowing for proactive business and facility management decisions. Some web based systems may even support multi utility metering points and come in handy for businesses operating multiple sites.

Whereas all this has been made possible by increased use of smart devices/ intelligent energy devices that capture data at more regular intervals; the challenge facing businesses is how to transform the large data/big volume of data into insights and action plans that would translate into increased performance in terms of increased energy efficiency or power reliability.

A solution to this dilemma facing businesses that do not know how to process big energy data, may lie in energy management software. Energy management software?s have the capability to analyse energy consumption for, electricity, gas, water, heat, renewables and oil. They enable users to track consumption for different sources so that consumers are able to identify areas of inefficiency and where they can reduce energy consumption, Energy software also helps in analytics and reporting. The analytics and reporting features that come with energy software are usually able to:

? Generate charts and graphs ? some software?s give you an option to select from different graphs

? Do graphical comparisons e.g. generate graphs of the seasonal average for the same season and day type

? Generate reports that are highly customisable

While choosing from the wide range of software available, it is important for businesses to consider software that has the capacity to support their data volume, software that can support the frequency with which their data is captured and support the data accuracy or reliability.

Energy software alone may not make the magic happen. Businesses may need to invest in trained human resources in order to realise the best value from their big energy data. Experts in energy management would then apply human expertise to leverage the data and analyse it with proficiency to make it meaningful to one?s business.

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