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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Which KPI?s to Use in CRM

Customer relationship management emerged in the 1980?s in the form of database marketing. In those tranquil pre-social media days, the possibility of ?managing? clients may have been a possibility although Twitter and Facebook took care of that. Modern managers face a more dynamic environment. If you are one, then what are the trends you should be monitoring yourself (as opposed to leaving it to others).

If you want to drip feed plants, you have to keep the flow of liquid regular. The same applies to drip-feed marketing. Customers are fickle dare we say forgetful. Denizon recommends you monitor each department in terms of Relationship Freshness. When were the people on your list last contacted, and what ensued from this?

Next up comes the Quality of Engagements that follow from these efforts. How often do your leads respond at all, and how many interfaces does it take to coax them into a decision? You need to relate this to response blocks and unsubscribes. After a while you will recognise the tipping point where it is pointless to continue.

Response Times relate closely to this. If your marketing people are hot then they should get a fast response to sales calls, email shots and live chats. It is essential to get back to the lead again as soon as possible. You are not the only company your customers are speaking too. Fortune belongs to the fast and fearless.

The purpose of marketing is to achieve Conversions, not generate data for the sake of it. You are paying for these interactions and should be getting more than page views. You need to drill down by department on this one too. If one team is outperforming another consider investing in interactive training.

Finally Funnel Drop-Off Rate. Funnel analysis identifies the points at which fish fall off the hook and seeks to understand why this is happening. If people click your links, make enquiries and then drift away, you have a different set of issues as opposed to if they do not respond at all.

You should be able to pull most of this information off your CRM system if it is half-decent, although you may need to trigger a few options and re orientate reporting by your people in the field. When you have your big data lined up speak to us. We have a range of data analysts brimming over with fresh ideas.

What Is Technical Debt? A Complete Guide

You buy the latest iPhone on credit. Turn to fast car loan services to get yourself those wheels you’ve been eyeing for a while. Take out a mortgage to realise your dream of being a homeowner. Regardless of the motive, the common denominator is going into financial debt to achieve something today, and pay it off in future, with interest. The final cost will be higher than the loan value that you took out in the first place. However, debt is not limited to the financial world.

Technical Debt Definition

Technical debt – which is also referred to as code debt, design debt or tech debt – is the result of the development team taking shortcuts in the code to release a product today, which will need to be fixed later on. The quality of the code takes a backseat to issues like market forces, such as when there’s pressure to get a product out there to beat a deadline, front-run the competition, or even calm jittery consumers. Creating perfect code would take time, so the team opts for a compromised version, which they will come back later to resolve. It’s basically using a speedy temporary fix instead of waiting for a more comprehensive solution whose development would be slower.

How rampant is it? 25% of the development time in large software organisations is actually spent dealing with tech debt, according to a multiple case study of 15 organizations. “Large” here means organizations with over 250 employees. It is estimated that global technical debt will cost companies $4 trillion by 2024.

Is there interest on technical debt?

When you take out a mortgage or service a car loan, the longer that it takes to clear it the higher the interest will be. A similar case applies to technical debt. In the rush to release the software, it comes with problems like bugs in the code, incompatibility with some applications that would need it, absent documentation, and other issues that pop up over time. This will affect the usability of the product, slow down operations – and even grind systems to a halt, costing your business. Here’s the catch: just like the financial loan, the longer that one takes before resolving the issues with rushed software, the greater the problems will pile up, and more it will take to rectify and implement changes. This additional rework that will be required in future is the interest on the technical debt.

Reasons For Getting Into Technical Debt

In the financial world, there are good and bad reasons for getting into debt. Taking a loan to boost your business cashflow or buy that piece of land where you will build your home – these are understandable. Buying an expensive umbrella on credit because ‘it will go with your outfit‘ won’t win you an award for prudent financial management. This also applies to technical debt.

There are situations where product delivery takes precedence over having completely clean code, such as for start-ups that need their operations to keep running for the brand to remain relevant, a fintech app that consumers rely on daily, or situations where user feedback is needed for modifications to be made to the software early. On the other hand, incurring technical debt because the design team chooses to focus on other products that are more interesting, thus neglecting the software and only releasing a “just-usable” version will be a bad reason.

Some of the common reasons for technical debt include:

  • Inadequate project definition at the start – Where failing to accurately define product requirements up-front leads to software development that will need to be reworked later
  • Business pressure – Here the business is under pressure to release a product, such as an app or upgrade quickly before the required changes to the code are completed.
  • Lacking a test suite – Without the environment to exhaustively check for bugs and apply fixes before the public release of a product, more resources will be required later to resolve them as they arise.
  • Poor collaboration – From inadequate communication amongst the different product development teams and across the business hierarchy, to junior developers not being mentored properly, these will contribute to technical debt with the products that are released.
  • Lack of documentation – Have you launched code without its supporting documentation? This is a debt that will need to be fulfilled.
  • Parallel development – This is seen when working on different sections of a product in isolation which will, later on, need to be merged into a single source. The greater the extent of modification on an individual branch – especially when it affects its compatibility with the rest of the code, the higher the technical debt.
  • Skipping industrial standards – If you fail to adhere to industry-standard features and technologies when developing the product, there will be technical debt because you will eventually need to rework the product to align with them for it to continue being relevant.
  • Last-minute product changes – Incorporating changes that hadn’t been planned for just before its release will affect the future development of the product due to the checks, documentation and modifications that will be required later on

Types of Technical Debt

There are various types of technical debt, and this will largely depend on how you look at it.

  • Intentional technical debt – which is the debt that is consciously taken on as a strategy in the business operations.
  • Unintentional technical debt – where the debt is non-strategic, usually the consequences of a poor job being done.

This is further expounded in the Technical Debt Quadrant” put forth by Martin Fowler, which attempts to categorise it based on the context and intent:

Technical Debt Quadrant

Source: MartinFowler.com

Final thoughts

Technical debt is common, and not inherently bad. Just like financial debt, it will depend on the purpose that it has been taken up, and plans to clear it. Start-ups battling with pressure to launch their products and get ahead, software companies that have cut-throat competition to deliver fast – development teams usually find themselves having to take on technical debt instead of waiting to launch the products later. In fact, nearly all of the software products in use today have some sort of technical debt.

But no one likes being in debt. Actually, technical staff often find themselves clashing with business executives as they try to emphasise the implications involved when pushing for product launch before the code is completely ready. From a business perspective, it’s all about weighing the trade-offs, when factoring in aspects such as the aspects market situation, competition and consumer needs. So, is technical debt good or bad? It will depend on the context. Look at it this way: just like financial debt, it is not a problem as long as it is manageable. When you exceed your limits and allow the debt to spiral out of control, it can grind your operations to a halt, with the ripple effects cascading through your business.

 

Still Looking For A Way To Consolidate Excel Spreadsheets?

We use Excel spreadsheets everyday. We use them to prepare budgets and reports. We even use them when drafting plans and forecasts. With this ubiquitous office application, entering data and carrying out on-the-spot computations and analysis is quick and easy. However, when it’s time to consolidate Excel data, I won’t be surprised if you wished there was an easy way.

In fact, you were probably looking for a solution before landing on this page, right?

Because budgeting, reporting, planning, and forecasting are normally done by a group of people and not just by one individual, spreadsheets bearing the necessary data can be scattered in different folders, desktops, offices, and, in the case of really large organisations, geographical locations.

How are these data brought together? Through email attachments or by sharing folders in a local area network. Each member of the working team sends out copies of their own spreadsheets to other members, who then review them, make necessary changes, then send back to the source. The files can go back and forth until everyone is satisfied.

With each sending, sharing, and edit, business critical data gets exposed to all sorts of spreadsheet risks. Copy-paste errors, omission of a negative sign, erroneous inputs, accidental deletions, and even fraudulent manipulations can take place. And because each member can end up with multiple versions of a single spreadsheet, the chance of working on the wrong version exists.

So when all the data gets consolidated and finalised, it is possible for the end product to contain significant errors. It may not happen all the time, but it certainly can happen.

But that’s not the only disadvantage of spreadsheets. The entire process of comparing cells and sheets, copy-pasting data, linking cells, writing formulas, and specifying ranges can be very tedious, not to mention time-consuming. With spreadsheets, beating deadlines is always an almost impossible exercise.

What you need is a solution that will no longer require you to consolidate Excel spreadsheets. One that is faster, more reliable, and significantly less error-prone. Denizon has a server-based solution that has all those capabilities and much more.

With a server-based solution, all your data is stored in one place. Everyone is working on the same data source, so consolidation is fast and easy. Everyone becomes synchronised and no one has to worry about working on the wrong version.

Read more about our server-based solution

 

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