Social media networks are creating large datasets that are now enabling companies and organizations to gain competitive advantage and improve performance by understanding customer needs and brand experience in nearly real time. These datasets provide important insights into real-time customer behavior, brand reputation, and the overall customer experience. Intelligent or “data analysis”-driven organizations are now monitoring, and some are collecting, this data from “propriety social media networks,” such as Salesforce Chatter and Microsoft Yammer and “open social media networks” such as LinkedIn, Twitter, Facebook, and others.
The majority of organizations today are not harvesting and staging data from these networks but are leveraging a new breed of social media listening tools and social analytics platforms. Many are tapping their public relations agencies to execute this new business process. Smarter data-driven organizations are extrapolating social media datasets and performing predictive analytics in real time and in-house.
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There are, however, significant regulatory issues associated with harvesting, staging, and hosting social media data. These regulatory issues apply to nearly all data types in regulated industries such as healthcare and financial services in particular. The SEC and FINRA with Sarbanes-Oxley require different types of electronic communications to be organized, indexed in a taxonomy schema, and then be archived and easily discoverable over defined time periods. Data protection, security, governance, and compliance have entered an entirely new frontier with introduction and management of social data.
This article provides a broad overview of the current state of analytical tools and platforms that enable accelerated and real-time decision making in organizations based on customers. Social media is driving organizational demand for insights on “customer everything” in addition to BI and analytics tools. Providing “enterprise BI” that includes social analytics will be a significant challenge to many enterprises in the near future. This is one of the primary reasons for the success of the new wave of innovative and easy-to-use BI and social media analytical tools within the last several years.
Social Media Analytic Tools Overview
In the beginning, there was SPSS and SAS Institute, the first analytical and statistical platforms to be computerized and go mainstream in the early 1980s. There is no way in my view you can talk about anything analytical without mentioning them. When I was a young marine scientist, these were the first DOS-based analytical tools we used to do basic statistical analysis in addition to rudimentary predictive analytics employed to forecast fisheries populations.
During the last 40 years, these platforms evolved to include a host of new capabilities and functionality and are now considered business intelligence tools. For the last 20 years, the majority of business intelligence tools accessed structured datasets in various databases, however now that nearly 80% of enterprise data is unstructured, many of the BI platforms incorporate sophisticated enterprise search capabilities that rely on metadata, inferences, and connections to multiple data sources. The vast majority of social media data is unstructured, as we know, and this presents significant challenges to many organizations in its overall management: collection, staging, archiving, analysis, governance, and security.
Many organizations today are leveraging their legacy business intelligence tools and platforms to perform analysis on social media datasets, in addition to the use of sophisticated tagging and automated taxonomy tools that make search (finding the right contents and/or objects) easier. The most basic and easy analytical tool used by nearly everyone is a simple alert, which combs/crawls the web for topics related to your alert criteria.
Modern capabilities of business intelligence tools and platforms
- Enterprise Search—structured and unstructured data
- Ad Hoc Query Analysis and Reporting
- OLAP, ROLAP, MOLAP
- Data Mining
- Predictive and Advanced Analytics
- In-Database Analytics
- In-Memory Analytics
- Performance Management Dashboards
- Advanced Visualization, Modeling, Simulation, and Scenario Planning
- Cloud and Mobile BI
Cloud-Based and Mobile BI and the New Innovative Business Intelligence Tools
Within the last several years, a new class of BI tools has emerged including some open source and cloud-based platforms/tools, some of which are specialized for specific vertical market segments or business processes. They are easy-to-use, highly collaborative via work flow, and some include standard and custom reporting in addition to including some rudimentary ETL tools. Mobile BI is one of the fastest growing areas; however, many legacy vendors have been slow to develop applications for BYOD, especially tablets.
These new products have innovative semantic layers and new ways of visualizing data, both structured and unstructured. In some cases, these new tools tout the fact that they can work with any database and don’t require the building of a data warehouse or data mart but provide access to any data anywhere. Innovative visualization dashboard platforms and implementations have been very attractive to business managers and have found their way into many organizations, in some cases, without the knowledge of the IT department.
In-Memory Database Technology is a Game-Changer
In-memory database technology, the next major innovation in the world of business intelligence and social media analytics, is the game changer that will provide the unfair advantage that leads to the competitive advantage every CEO wants today. In-memory technologies and built-in analytics are beginning to play major roles in social analytics. The inherent business value of in-memory technology revolves around the ability to make real-time decisions based on accurate information about seminal business processes such as social media.
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