Leveraging Big Data in the Modern Tax Function
by Terri Eyden on
Data management and collection
The use of a centralized repository to house structured data is not a new concept, but it remains an effective and critical solution. One of the persistent struggles facing tax departments today is efficiently using data stored across multiple systems on varying platforms, many of which were designed without taking into account the needs of the tax department. Consolidating tax data into a data warehouse is an important first step toward a meaningful data management solution. Data warehouses provide the ability to maintain a single version of the truth and eliminate the risk of data getting out of synch between systems.
Data warehouses may be as broad as a mainframe solution that captures all of the relevant data maintained within the organization, or it may be focused on a single functional area such as the tax department.
Hand in hand with a data warehouse are ETL tools. The acronym ETL refers to Extract-Transform-Load, and as the name suggests, these tools provide the ability to collect data from disparate sources and transform it into a standard format for analysis and reporting. ETL tools are flexible enough to accommodate various data types and platforms while ensuring a consistent definition and use of the data that is collected. On their own, these tools may also offer the opportunity to overcome challenges presented by legacy systems, which are not configured to accommodate the needs of the tax department by automating the retrieval of critical information into downstream databases or tools for use in tax-oriented analysis and reports.
Big data is made up of structured and unstructured information. Structured data is typically found in databases and accounts for 10 percent of the big data that organizations possess. The other 90 percent is made up of unstructured data, such as e-mails, call center recordings, social media posts, and website logs. Organizations are faced with the challenge of translating all of this data into meaningful content in an efficient manner that allows for effective decision making.
Data warehouses and ETL tools open the door for effective data mining. "The era of big data brings new data management and data mining challenges, but just as many opportunities. The more data that exists and the more that data is in chaos, the more important translation systems are to future success. We rely on IT to manage these translation systems and to innovate and improve on both the systems and the translation processes" (TechNet Magazine, "IT Management: The Petabyte Era).
Data mining tools are used to identify the relevant and meaningful pieces of information within a dataset, a capability that is becoming increasingly important with the emergence of big data. As an example, text mining of keywords, tags, and patterns or terms in both structured and unstructured data, such as paper documents, can help identify US citizens to meet new FATCA reporting requirements. Data mining provides a chance to highlight areas requiring deeper analysis and investigation to help minimize the risk of negative tax impact from proposed business decisions. However, this analysis is only as good as the data itself. Data must be organized and stored at a sufficient level of detail to create meaningful value from data mining.
Business intelligence and data discovery
As a next step, once data has been gathered and organized, business intelligence solutions and data discovery tools provide the functions to turn raw data into valuable results. Business intelligence (BI) solutions include the dashboards, analytics, and reports that allow tax departments to leverage the large amounts of structured data maintained in data warehouses.
One of the most important components of BI is customizable dashboard views that provide the opportunity to organize and present data visually at varying levels of detail depending upon the intended audience. Given the vast quantities of data available, this type of solution is essential to distill the important pieces of information and present them in a way that is meaningful to each user. Dashboards offer the opportunity for collaboration and integration across the organization by making tax data and analysis visible to other departments and all levels of the organization in a way that they can easily digest in real time as the data is captured.
Predictive analytics is a specific branch of BI analysis that uses elements called predictors to create models that can be analyzed to forecast future probabilities. The models are revised or validated as new data becomes available. Predictive analytics are a valuable tool for data-driven decision making by offering the ability to identify trends and evaluate the tax or financial impact of potential business decisions.
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2 weeks 4 days ago by claudilocks