Everyone is talking about a data explosion:
- RFID information in Retail environments
- Social media interactions via wireless
- Behavioral event data via eCommerce
All of this is leading toward the era of “big-data”. Most would say that the “big-data” era is already upon us. Some would say that future data loads will dwarf current requirements just as current numbers dwarf the past 5–10 years.
However, the key to the “big-data” era will not be in the simple accumulation of data in business intelligence and data warehousing (BI/DW) environments, but the utilization of that data across the organization.
Deep Analytics on Big Data
This week The Data Warehousing Institute (TDWI) held its initial solution summit on the topic of “big-data” in San Diego: Deep Analytics for Big Data. It was a gather of decision makers and leading vendors to discuss the topic of “big-data” and the future of analytics associated with those “big-data” BI/DW environments.
Chief among the discussion topics were how to make the correction decisions on:
- Building “big-data” environments in a greenfield environment
- Transitioning from existing BI/DW environments to support “big-data”
- Hybrids to support existing datasets and the “new”, larger requirements
Solutions. Not just Problems.
During the solution summit, customer implementation case studies were provided by vendors that highlighted the issues with “big data” BI/DW engagements.
- Tableau showed the need to provide data visualization on “big data” in a timely manner
- Teradata demonstrated how the value of the analysis was at least, if not more, important than the size of a “big-data” environment
- Aster Data highlighted the speed at which “big-data” analytics were required.
- HP talked about the new automated action requirements from “big-data”
- Kognitio detailed how their customers are finding new revenue streams from “big-data” analytics.
Telecom organizations are on the front line of “big-data” analytics. Wireless voice, SMS and IP-base product data are at the core of the “new” business models for both carriers and organizations looking to capitalize on new business models…
Think about it… All the information that Google uses for their targeted web-based advertising transits a telecom network at some point. iTunes would not be possible without the networks to pass content to either the tablet or smartphone. Carriers need to use their knowledge of the network events linked with customer information to either get a leg up on companies like Google and Apple.
Yet, carriers should exercise good judgment with all that “big-data”. Privacy laws associated with customer information are only going to become more stringent in the future as uses like telematics and location-based services take hold.
How is your telecom organization tackling “big-data”? Reactively or with strategy?
Post your comments below or email (John.Myers@BlueBuffaloGroup.com) / twitter (@BlueBuffaloGrp) me directly.
Posted October 6, 2010 7:00 PM
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