Big data strategy: 5 areas to reassess by mid-2018
At the start of 2018, I mentioned five priorities that companies should have
in their 2018 big data strategic plans These were storage,
architecture, demystification, operationalization and analytics as
everyday business.
These priorities still hold—because if employees at all levels in your company don't understand why you are working with big data, and haven't yet seen how this data can be put to use for the business, your big data projects are failing.
One other thing to keep in mind is that strategic planning about anything is no longer the same. You simply can't roll out one to three year plans and then measure against them as time goes by without making adjustments.
Today, strategic planning moves at the same rate of change as business and markets. Managers must continuously revisit plans to see where there is "drift" from the original plan, and what they need to do to realign it with the rate of business and market change.
With the first quarter of 2018 coming to an end, now is an excellent time to reassess the 2018 big data plan you started with to see if adjustments are needed.
What you are likely to find is that your start of year priorities haven't changed much—but that there are certain tweaks that have to be made to stay on course.
Here are five areas to pay attention to:
As companies move toward collecting data on drones, sensors and other field-based technology, internet bandwidth constraints will lead them to storing the collected data locally, instead of attempting to transmit all data in real time to a central location. Going into 2018, common thinking was that much of this collected data would be sent to public clouds for storage. This is still the case, but bandwidth constraints affect cloud-based storage, too. The strategy adjustment for many companies will be a return to traditional distributed storage, where data locally collected is stored on field-based servers and/or disk.
These priorities still hold—because if employees at all levels in your company don't understand why you are working with big data, and haven't yet seen how this data can be put to use for the business, your big data projects are failing.
One other thing to keep in mind is that strategic planning about anything is no longer the same. You simply can't roll out one to three year plans and then measure against them as time goes by without making adjustments.
Today, strategic planning moves at the same rate of change as business and markets. Managers must continuously revisit plans to see where there is "drift" from the original plan, and what they need to do to realign it with the rate of business and market change.
With the first quarter of 2018 coming to an end, now is an excellent time to reassess the 2018 big data plan you started with to see if adjustments are needed.
What you are likely to find is that your start of year priorities haven't changed much—but that there are certain tweaks that have to be made to stay on course.
Here are five areas to pay attention to:
1. Data storage for field-based technology
As companies move toward collecting data on drones, sensors and other field-based technology, internet bandwidth constraints will lead them to storing the collected data locally, instead of attempting to transmit all data in real time to a central location. Going into 2018, common thinking was that much of this collected data would be sent to public clouds for storage. This is still the case, but bandwidth constraints affect cloud-based storage, too. The strategy adjustment for many companies will be a return to traditional distributed storage, where data locally collected is stored on field-based servers and/or disk.
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