It's been a while since I've posted. The hiatus is not because I have not had anything to say (that's never an issue!). I've been involved with a strategic assessment for a client who wants to combine big data and data warehousing/bi. Lots of thinking...exciting stuff!
This client is not a social media giant and neither are we! The client does not have a customer retention problem. In fact, they have more customers than they can handle. So why would they want to get into big data. Part of the shift is driven by products/vendors pushing them towards big data analytics. And the rest is driven by the need to attract the best customers.
The strategy work we are doing is challenging. Of course, we want to position the client for the future where big data is not a "wish to have" but a "must have". And we want to position them to attract the best customers and leverage current intellectual capital to tap shrinking sources of R&D. At the same time, we want to make sure that they can analyze their structured data in meaningful ways to assess performance relative to historical trends, external factors, and corporate goals.
In this light, what are the best recommendations? With customers increasingly moving to a combination of traditional and cloud-based systems and services...how is the concept of an integrated data warehouse changing? How do you combine structured and unstructured data to foster good decision making without making data scientists of the average corporate manger? How do you structure your organization? How do you build capacity? What do you keep in-house, when do you use the cloud....all interesting questions with no one-size-fits-all answers except this: if you aren't thinking about all this, it's time to start now.
This client is not a social media giant and neither are we! The client does not have a customer retention problem. In fact, they have more customers than they can handle. So why would they want to get into big data. Part of the shift is driven by products/vendors pushing them towards big data analytics. And the rest is driven by the need to attract the best customers.
The strategy work we are doing is challenging. Of course, we want to position the client for the future where big data is not a "wish to have" but a "must have". And we want to position them to attract the best customers and leverage current intellectual capital to tap shrinking sources of R&D. At the same time, we want to make sure that they can analyze their structured data in meaningful ways to assess performance relative to historical trends, external factors, and corporate goals.
In this light, what are the best recommendations? With customers increasingly moving to a combination of traditional and cloud-based systems and services...how is the concept of an integrated data warehouse changing? How do you combine structured and unstructured data to foster good decision making without making data scientists of the average corporate manger? How do you structure your organization? How do you build capacity? What do you keep in-house, when do you use the cloud....all interesting questions with no one-size-fits-all answers except this: if you aren't thinking about all this, it's time to start now.
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