The term Innovation is often misunderstood. Without innovating, enterprises fail, waste your time and money, and often take away livelihoods.
While fossil fuels are becoming a realistic energy source for private use, it is important to note how K Sridhar of Bloom Energy made a few tweaks to the ordinary approach one takes.
The use of color and hard "paper" (which is actually baked beach sand) made a really big difference if you remember the video in my previous post. Now, companies, no matter how huge, can power their facilities with Bloom Energy installations.
Clean energy is finally here, but what about foolproof data?
One thing's for sure: If your data business has to earn money that is enough to install a Bloom Energy power box, it better does some genuinely good business.
Innovative approaches are seldom effective, unless they are both, timely and targeted. It simply means that a new algorithm may hardly work as expected. It is the little tweaks that you make in the data algorithm after practical use and failure, that can take your innovation to a level of newsworthiness.
Algorithms for uplifting big data businesses are evolving fast. So fast and thick, that the demand for them seems to be creating a deluge of average stuff. While that is always the case in every open market, an alarmingly low number of effective solutions is what could awaken you. Awaken you enough to keep an eye for what really is innovation.
So the next time you are buying from a promising source, make sure it is at least an experienced one. Because someone who hasn't made a mistake, is probably just about to make one!
We made mistakes through the first decade (2003-07), losing value for data and what we procured thinking will stay good for a few years. Then we brought in regular updating, which still remains unmatched and unique, and supplemented by a manual component. The manual process is driven by a list of rules, which enable callers to maximize the number of verifications made in a day.
What followed was relational data-accuracy algorithms. Collating a number of techniques of data sorting and large-database solutions, we came up with innovations that allowed the simplest interfaces, providing search access to influential decision makers and people who are likely to purchase in the B2B arena. What's better? The information is real-time!
Some innovations can be easily perceived, sometimes mundane, but just impossible to implement. Big data is one such arena. However, Procure Data has proved to be a game changer by implementing verification, cleansing, overall management, and manual processes under one umbrella - so that you can get what it takes to find new and highly relevant clients
While fossil fuels are becoming a realistic energy source for private use, it is important to note how K Sridhar of Bloom Energy made a few tweaks to the ordinary approach one takes.
The use of color and hard "paper" (which is actually baked beach sand) made a really big difference if you remember the video in my previous post. Now, companies, no matter how huge, can power their facilities with Bloom Energy installations.
Clean energy is finally here, but what about foolproof data?
One thing's for sure: If your data business has to earn money that is enough to install a Bloom Energy power box, it better does some genuinely good business.
Innovative approaches are seldom effective, unless they are both, timely and targeted. It simply means that a new algorithm may hardly work as expected. It is the little tweaks that you make in the data algorithm after practical use and failure, that can take your innovation to a level of newsworthiness.
Algorithms for uplifting big data businesses are evolving fast. So fast and thick, that the demand for them seems to be creating a deluge of average stuff. While that is always the case in every open market, an alarmingly low number of effective solutions is what could awaken you. Awaken you enough to keep an eye for what really is innovation.
So the next time you are buying from a promising source, make sure it is at least an experienced one. Because someone who hasn't made a mistake, is probably just about to make one!
We made mistakes through the first decade (2003-07), losing value for data and what we procured thinking will stay good for a few years. Then we brought in regular updating, which still remains unmatched and unique, and supplemented by a manual component. The manual process is driven by a list of rules, which enable callers to maximize the number of verifications made in a day.
What followed was relational data-accuracy algorithms. Collating a number of techniques of data sorting and large-database solutions, we came up with innovations that allowed the simplest interfaces, providing search access to influential decision makers and people who are likely to purchase in the B2B arena. What's better? The information is real-time!
Some innovations can be easily perceived, sometimes mundane, but just impossible to implement. Big data is one such arena. However, Procure Data has proved to be a game changer by implementing verification, cleansing, overall management, and manual processes under one umbrella - so that you can get what it takes to find new and highly relevant clients
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