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Data Replication

Medical Data Form

These days, not many companies can continue to operate once their entire computer system goes down. All the information needed in daily operations are stored in databases while the interfaces that make use of them all come in the form of software applications.

Software applications can be rapidly reinstalled and configured for as long as the necessary programs are available. Data, however, cannot be reconstructed as quickly even with hard copies available. It is therefore necessary to store your data in a replicated setup so that when one section goes down, operations can proceed without interruption.

For instance, if a category 5 hurricane renders your main office useless, you can simply rent workstations elsewhere, connect to the Internet and continue with your usual transactions for as long as data is readily accessible.

So how do we ensure the accessibility and reliability of your data? Here’s what we’ll do:

  • Activate data replication on your database management system. If your DBMS does not support replication, we’ll migrate all your data to one that does.
  • If absolutely necessary, we can allow modernised systems to run parallel to your legacy systems and prepare both for full modernisation when you’re ready.
  • Implement fail-over technologies where applicable to provide for automatic switching to a backup data server or network from one that has just failed.

We can also assist you with the following:

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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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Is Your Project Agile, a Scrum or a Kanban?

Few projects pan out the way we expect when starting out. This is normal in any creative planning phase. We half suspect the ones that follow a straight line are the exceptions to the rule. Urban legend has it; Edison made a thousand prototypes before his first bulb lit up, and then went on to comment, ?genius is 1% inspiration, 99% perspiration?. Later, he added that many of life’s failures are people who did not realise just how close they were to success when they gave up.

So be it to this day, and so be it with project planning too. There is no one size fits all approach when it comes to it. Agile, Scrum and Kanban each have their supporters and places where they do well. Project planning often works best when we use a sequential combination of them, appropriate to what is currently happening on the ground.

Of the three, Agile is by far the most comprehensive. It provides a structure that begins with project vision / conceptualisation, and goes as far as celebration when the job is over, and retrospective discussion afterwards. However, the emphasis on daily planning meetings may dent freethinking, and even smother it.

Scrum on the other hand says ?forget all that bureaucracy?. There is a job to do and today is the day we are going to do it. Although the core Agile teamwork is still there it ignores macro project planning, and could not be bothered with staying in touch with customers. If using Scrum, it is best to give those jobs to someone else.

The joker in the pack is Kanban, It believes that rules are there to substitute for thought, and that true progress only comes from responsible freedom. It belongs in mature organisations that have passed through Scrum and Agile phases and have embarked on a voyage towards perfection.

That said, there can be no substitute for human leadership, especially when defined as the social influence that binds the efforts of others towards a single task.

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