Almost every business and technology discussion these days starts with rapturous and/or concerned statements about the explosion of data that surrounds and often threatens to overwhelm us. Whether it be structured or unstructured, real time or historical, mobile, social or enterprise … the exponential volume and variety of data is not news to anyone.
The challenges = and the opportunities as well = are also well known and understood by business leaders, technology specialists and each of us as individuals. To capture the views of our clients, HP commissioned an independent study conducted by Coleman Parkes in October 2011 using 554 telephone interviews among senior business and technology executives in Enterprise-level companies (including public sector) around the globe to understand their information management challenges, priorities, and perspectives. What we found…. 50% of executives believe that they do not have an effective information strategy in place—a strategy that cuts across organizational silos, technologies and strategic functions. Only 2%report that they can deliver the right information at the right time to support the right business outcome 100 percent of the time. 34% of respondents indicated that more than 50 percent of all the information within their organization remains unconnected, undiscovered and unused. 35% of respondents indicated they were not effective at accessing business information as and when needed for legal/compliance and operational needs.It’s clear that enterprises must connect information and intelligence across the business ecosystem to advance competitively. Velocity (speed!) must be combined with the volume and variety of data to ensure that they capitalize on every possible competitive advantage.
SLIDE OBJECTIVE – to highlight the presence of Extreme Information and its implicationsKEY POINTSWe highlighted earlier the tremendous VOLUME of information being created. But Gartner and others also have shared their findings and observations around the emergence of ‘Extreme Information’, which also involves three other complicating dimensions to information.Along with Volume, there’s the VELOCITY. Relevant, valuable information for an enterprise is coming at such a torrential pace it’s become a real-time phenomenon requiring real-time capabilities.Next is VARIETY – which you can see from just the subset of information sources shown here.Finally there’s the COMPLEXITY of where it lives and moves. From server to cloud to hybrid to device and back and forth.
Use this telco example to highlight:CRM data married with Extreme network CDR data for precision point churn analysis, promotion, retention joined againstMeaningful unstructured information for exact targeting at the individual level.Much better modeling and targeting can be achieved when combining all of this.
SLIDE OBJECTIVE: Analyzing and mining social media to drive business value; revenue and competitive advantage.KEY POINTS: Groupon’s making the most out of its millions of users, and analyzes its big data to determine the effectiveness of its advertising expenditures, consumer behavior as well as purchaser demographics and location. Groupon analyzes its data to create more personalized offers and is targeted to particular consumer interests have generated more purchases per customer. Groupon’s data analysis has led to better marketing insights on customer habits and preferences and delivers it as a service back to their merchants.The New York Jets launched their Ultimate Fan game in September 2010, which was the first revenue generating Facebook app to be backed by a pro sports team. The application lets football fans do online what they would normally do at home and in stadiums—root for their favorite teams and players, predict game scores, and hold a virtual tailgate party with other fans from across the globe. The Jets are able to engage with their fans and make them feel like they are part of the team. They are leveraging social medial to capitalize on their fans' passion for the team and their willingness to share that fervor. PETCO is yet another example. The company provided a promo code to their customers for $40 in free shipping. The person who shared their code with the most people won a $500 PETCO gift card. About 40 percent of the sales that resulted from this promotional push came from new consumers. The desire to save a few dollars on shipping costs drove loyal PETCO customers to connect with the larger pet owner community and spread the word about the store via social media.
Key Thoughts:Augmenting Vertica’s strengths in high performance in-database sessionizing, page rank, user activity and pattern matching, Vertica now supports high performance in-database web server log parsing. With the web package, Vertica directly imports web server logs from Microsoft IIS and the open WC3 format (produced Apache and many commercial products). This both eliminates the requirement for external applications, and reduces the latency between online events and final analysis. Vertica customers leverage the dense encoding and compression of the Vertica platform to retain the detailed history needed for detailed profiling. Results from deep analysis of trends and ranking, as well as identification of high value customer segments, can feed directly into models used by dynamic content applications for a personalized and highly engaging web experience.
Key Thoughts:Within the XML and Sentiment Analysis Packages you’ll find the access libraries used by the developer’s example code – and these are full fledged packages themselves, enabling Vertica to retrieve some of the most relevant external data sources for brand management and online marketing available today. Armed with these resources, refreshed on demand and served up with minimal latency, you’ll immediately empower your Corporate Communication Strategy with the facts that differentiate your brand focus and marketing.
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At Vertica, our vision was clear. From the very first line of code, Vertica was purpose built to change the conversation from the massive challenges of big data to the massive opportunities from the answers that big data can provide. To do this, we focused on handling data VOLUME, ensuring all VARIETY of data could be managed, transforming the concept of VELOCITY and doing it all on commodity hardware with the highest possible storage compression to ensure maximum VALUE. UnlimitedVOLUME and VARIETYStructured, semi-structured, log data, flat files, machine data, small text (64K or less)Linear scaling by adding more resources on the flyNative support for MapReduce and HadoopVELOCITY provides answers in near real time Columnar storage & execution Spin up extreme data stores in mins/hours, not days/monthsLoad and query simultaneouslyPerforms queries 50X faster by eliminating costly disk I/ORuns nonstop with performance optimized data replication, failover and recoveryVALUE is unmatched due to: Aggressive data compression reduces storage costs by > 90%Commodity X86 hardware, preconfigured appliance or via the cloud Scalable MPP design on Commodity Infrastructure
Be proactive versus reactiveAnalysis of transaction data can provide a retroactive means of detecting fraud, but real-time use of transaction data can proactively step in to stop fraud.
Using big data analytics to monetise and link customer experience and direct marketing to profitability