For a few years now, data visualization is the buzz word in the IT industry. Although the concept of presenting complicated data in a more business friendly way is not new, the increasing business need for fact-based decision making has added a new urgency in adopting tools that can help business users access the data on their own without heavy reliance in IT. Some of the leading vendors in this area are Tableau, Qlick, Tibco/Spotfire and Micro Strategy. All of these tools provide business users a quick way to relate to their data without too much reliance on IT.
With data visualization tools, users can put face to otherwise obscure business data. If business users understand the data, they can quickly, without much help from IT, connect to this data and start building their own reports and dashboards. A very easy-to-use and suggestive user interface allows business users to put together a fancy looking informative dashboard in not time. However the key phrase here is “understand the data." Not all users are data savvy. In order to use the data visualization- aka data discovery tools- one must understand the nomenclature of data. Otherwise they are still dependent on IT to provide them with data views and data extracts, which increases IT involvement and in turn kills the whole purpose of these tools; to provide self-reliance for business users.
One major drawback of connecting to raw data is that intelligence is built at the report level. If there is no standardized semantic layer across the organization, data is manipulated, aggregated and formulated at the report level. This can compromise single version of the truth that every organization aims to achieve. Although some will argue that there are ways to create centralized views of the data within these tools, these views are subjective and in some cases require duplicated effort between multiple departments based on their needs.
Cross functional reporting (combining multiple data sources in single view) and scalability (sharing single report with multiple groups with data level security) are also few challenges that need to be overcome early in design session when implementing these tools.
In summary, my take is that data visualization tools are great for departmental level reporting needs. Sometimes a business cannot wait for IT to provide them with centralized view of their data. These tools come in handy with analysts and decision makers to quickly make sense of their data and define their KPIs. Yet eventually, KPIs and sources should be incorporated with enterprise reporting architecture for scalability, common view of enterprise data and self-enablement of not-so-data-savvy users.
In the next installment of this blog, I will discuss the some of the key features of enterprise reporting and perform a comparative analysis of a couple of leading enterprise reporting tools and data visualization tools. Stay tuned…