The Big Data, Big Spending Conundrum - Why They Are Not Always a Pair
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Big Data, a situation where an enterprise or group has a very large amount of data it must deal with through its database system, is often associated with Big Spending on those database solutions. More often than not, this is the case. In the case of health care, for instance, the reams of data that are produced daily and that must be cataloged, stored, protected, and retrieved on demand mean that the health care industry in general spends more than any other (on a business-by-business level) on their database management. The financial industry also ranks high up on the list of Big Data, Big Spenders.
If your company produces a lot of data, however, it does not necessarily mean that you have to be a big spender to manage it. Although the enterprises that have Big Data but avoid Big Spending are the exception rather than the norm, this has more to do with the fundamental misconception in the database administration (DBA) and information technology (IT) fields than it does in scaling and costs.
Before we look at how this can be changed and why your company's IT budget doesn't have to be busted because of your DBA needs, let's look at what, exactly, Big Data is. This is important to understanding the options available that can manage Big Data without draining the bank account.
Wikipedia defines Big Data as: "datasets that grow so large that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing."
What that means is that, quite often, companies can produce a lot of data by virtue of their business itself. It's becoming more and more common because not only are more things becoming digitized and stored as part of a database, but more and more is being created just because it's available and potentially useful. For instance, a client we work with is in the business of brokering seafood in Canada. Just a couple of years ago, most of their data involved supplier and buyer information and transportation logistics along with inventory projections (since seafood is an on-time commodity).
This generated a fair amount of data, but was easy to manage because it was all basically linear. Supplier and buyer information was a "static" bit that changed little while the other datasets, such as supply-demand and logistics, flowed around them. So there was a clear beginning and end to the datasets being used because everything had an obvious place in dataset's landscape.
Today, that same company is still tracking buyer, seller, inventory, etc. However, now new additions including weather predictions, market changes, currency valuations, added logistics because of new clientele in the United States, and more have all been added. Their database has literally quadrupled in only two years. All of this data flows around and is not necessarily linear anymore. Sales and deliveries in Canada are not affected by logistics and currency exchanges that sales in the U.S. are. Further, the market trends and weather data (which changes supply expectations) often affect future sales demands, but may or may not affect current sales and inventory.
In short, this client has a lot of new information to handle and a traditional, old-style database was no longer enough to handle the workload. Yet when we upgraded their system to a more robust solution, we didn't break the bank. Why? Because despite their industry not having a specific solution for their needs, there was one in another industry that was similar and required only minor tweaking to make it work. That solution meant a much more affordable implementation that still covers everything required, has the ability to expand with the business, and that is tried-and-tested already so maintenance is minimized.
Frankly, most solutions offered by many DBAs are over-engineered, over-priced because they are industry-specific (and marketed as such), or have high service fees attached to them because the solution provider requires you to hire their in-house staff because of the propriety of the database.
All of this can be avoided if the opinion of a neutral third-party DBA is sought and if the administrator who is doing the work is both up-to-date with the database industry and flexible enough to see solutions that are outside the box. |
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Author Resource:-
[About] The DBA Shoppe specializes in remote DBA services for clients with Oracle, DB2 and SQL Server databases. Providing certified Database Administrators for your day to day requirements, the DBA Shoppe saves you time and money. How healthy are your databases? Discover today at http://www.TheDBAShoppe.com
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By :
Jacomus Beresford
Submitted
2011-11-20 07:52:32 |
Article From Article Mayhem
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