This Forbes article includes some great examples of business models evolving to make money and improve our lives through mining and sharing data. The businesses are not making money immediately but are investing in data capture, analytics and partnerships to start capitalizing on their data for long term revenue.
Key points in the article:
- Your data combined with those of thousands of other people can tackle bigger problems such as cutting your company’s health care budget or sparing the nearby utility from building another power plant.
- Smart-thermostat maker Nest Labs has quietly built a side business managing the energy consumption of a slice of its customers on behalf of electric companies.
- In wearables, health tracker Fitbit is selling companies the tracking bracelets and analytics services to better manage their health care budgets, and its rival Jawbone may be preparing to do the same.
- These companies are capitalizing on the terabytes of data they collect from consumers and, to an extent, on the largesse of taxpayers. State governments have increased the money–from $1.3 billion in 2003 to $6 billion in 2012–allocated to helping utilities manage energy demand, according to the U.S. Energy Information Administration.
See full article - http://www.forbes.com/sites/parmyolson/2014/04/17/the-quantified-other-nest-and-fitbit-chase-a-lucrative-side-business/
How can we leverage our data either directly or with business partners/customers to generate revenue and solve big problems?
We know we have data which we can leverage as an asset. We also can derive great insights or predictions for our customers. In this article it describes what start-ups are doing to build a winning BI business model in this middle market. I like the intercept/middleware model mentioned near the end of the article. CDF is looking at potentially playing in that space or partnering with other companies that offer services to dealers and capture additional data from the dealers.
The Gartner report was released a few months ago. I was looking for an objective review of their quadrant and who was gaining ground and who was losing ground. I found this excellent summary with insightful commentary. Link
Gainers: Tableau, Qlik and Spotfire. Losers: Microsoft, MicroStrategy, SAP and Oracle.
We don’t need more tools right now but we do need to keep an eye on the future for when we might want to retire a tool or move more solutions to a tool we already have.
Hope you find the analysis informative
Big Data is not making the Data Warehouse obsolete overnight. The apostles of the Data Warehouse have fought back and demonstrated that it is not always as simple as “load and go.” Although some data engineering has been eliminated or reduced, and Big Data approaches are reducing the costs of data management, data still needs to be standardized, data quality maintained, and access provided to constituent communities. Data management will continue to be an evolutionary process.