3. Your End Users Can Visualize Data
While the business intelligence software market is relatively mature, a big data initiative is going to require next-level data visualization tools, which present BI data in easy-to-read charts, graphs and slideshows. Due to the vast quantities of data being examined, these applications must be able to offer processing engines that let end users query and manipulate information quickly-even in real time in some cases. Applications will also need adaptors that can connect to external sources for additional data sets.
Usability is another consideration. CFOs, CMOs and other non-IT executives are looking to leverage data, so they need access to charts, infographics and dashboards. Fortunately, leading BI vendors are shifting from an IT-driven to self-service analytics model that puts business users in the driver's seat. This accelerates adoption as well as return on investment and expands analytics' reach beyond report writers and more technical end users.
4. Your Company Can Find New Business Opportunities
As big data analytics tools continue to mature, more users are realizing the competitive advantage to being a data-driven enterprise. The 2012 presidential election demonstrated this. Campaign managers in both the Democratic and Republican parties saw a critical need for information on voters and their specific interests; taking this info and addressing an issue through a customized email or flyer meant the potential to gain or sway a vote.
Information regarding our preferences, likes and dislikes is critical to more than just political candidates. Social media sites have identified opportunities to generate revenue from the data they collect by selling ads based on an individual user's interests. This lets companies target specific sets of individuals that fit an ideal client or prospect profile.
Finally, big data use cases in about in retail, where the focus is on gaining insights by studying consumer behavior in online stores or physical shopping centers.
5. Your Data Analysis Methods, Capabilities Will Evolve
Data is no longer simply numbers in a database. Text, audio and video files can also provide valuable insight; the right tools can even recognize specific patterns based on predefined criteria. Much of this happens using natural language processing tools, which can prove vital to text mining, sentiment analysis, clinical language and name entity recognition efforts.
One example that highlights the use of audio analysis and big data comes from MatterSight. This call center tool can match incoming caller to the appropriate customer agent by using predictive behavioral routing and other analytics technology. MatterSight performs audio analysis to identify and score the calls based on specific criteria and then match customers with the best department to ensure the best experience. These advanced capabilities highlight some of the advancements we continue to see in unstructured data analysis and Big Data capabilities.
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