The fastest growing aspect of any modern business is its data enterprise. How a business mines, organizes and analyzes data is tantamount to that business’ success, and in the digital age, there’s no shortage of data. That’s why it’s becoming increasingly important that a business has a data management plan to handle, digest and make decisions based on the Lovecraftian amount of data streaming in every second.
But having a plan isn’t enough in the modern business environment. A savvy CTO needs the right team and software backing up their plan. That’s where installation testing -- and the software engineering team behind it -- comes in. Any good business needs both a plan and the right team in order to realize a successful data management strategy and watch their success manifest.
Data management and what it can do for you
As we said, data has quickly become one of -- if not the -- most important asset to a business’ success. Modern day enterprises are having to stop, reevaluate and make changes in order to keep pace so as to not fall behind. Many businesses have made arrangements to handle simply greater volumes of data, but that’s simply not enough. The nature of our current economy is such that businesses must also account for:
A wider variety of data formats,
Complex data storage strategies,
Analytic and organizational strategies (because you need to be doing something with the data), and
How the data and analytics are translated into business insight and strategy.
This is what a data management strategy should be doing for you. It’s why you need a data management strategy.
Any good strategy will address:
And any good strategy will achieve:
Higher Data Quality
Better Business Insights -- which result in better business decisions
Improved Data Security
Why hybrid data management?
To understand hybrid data management better, it is important to understand the differences between traditional and emerging data & analytics platforms.
Key differences between traditional & emerging data management approach include:
As it’s quite apparent from the above comparison, there are advantages and disadvantages for each approach. This drives the need for embracing a hybrid data management approach, so you can have the best of both worlds.
A business would be wise to also consider:
Mixed analytical work-loads
Long-tail usage of traditional data platforms as change to emerging is not easy
Time-spent on data preparation & movement rather than transformations and analytical processing
All of which absolutely necessitate the use of hybrid systems. A single form simply cannot deliver the needed range of flexibility these require.
Hybrid approaches can scale with the growing enterprise needs, increase agility, enable innovation, increase predictability, improve forecasting accuracy, detect new behavioral patterns and deliver analytical insights relevant to the business processes and applications. It’s simply a no-brainer. Whichever way you decide to manage your business’ data, a bespoke hybrid plan is the only way to go.
How to deploy Hybrid Data Management?
Deploying hybrid data management can be started anytime based on the immediate business need or a challenge like growing data volume and limitation with a physical data center/platform setup. Some other considerations before deploying include:
Impact on current technical landscape which includes impacts on on-site infrastructure, data availability, data access, data movement & processing
Impact on business processes
Technology choices & adoption
The diagram above illustrates a hybrid data management architecture plan for a data warehouse and a data lake platform; however, it is not limited to what’s in the diagram. Think of this as a base example. Any strategy you and your team choose can be customized to fit your business needs by the right software engineering team.
The hybrid data management combines the features from both the traditional and emerging platforms. For example, the following combinations can be incorporated as shown in the above diagram.
On premises + Cloud
Structured + Unstructured data
Enterprise Data Sources + External Source APIs like Social Media, Weather, etc,
SQL + No SQL
Data warehouse + Data Lake
Commodity + Open Source
In principle, it’s extremely important for a CTO to look at a hybrid data management strategy so as to enable business with a robust data & analytics platform that drives agility, quality of data and insights to run and grow the business.
Installation testing and why it’s so vital
We saved the most important aspect of this whole process for last. Ultimately, no strategy can be first built and finally implemented without the incredibly key step of installation testing.
Installation testing is exactly what it sounds like: the testing required to properly install and implement applications and software updates. On a small scale, you’ve gone through it before. Whenever you’ve downloaded an app on your phone there’s been some kind of installation testing happening to make sure things are going smoothly and the app will function properly. On a larger scale -- say the enterprise level --this testing is much more complex and should have a team of software professionals overseeing the process.
Without the proper installation testing being done the entire strategy can go awry. Different systems can become redundant and slow the network as a whole. Software already being used in the network can complicate the installation of a new software. Any number of things can happen and go wrong when it comes to mixing and marrying software, and the only way to make sure your business continues to run smoothly is with the help of an experienced software engineering team at your side. That’s why it’s absolutely crucial when writing and implementing your data management strategy you first ensure installation testing will be a major factor in that strategy.