Implementation of analytics programs often fails due to the lack of or low quality of available data. The first action Rainmaker BA performs on a new client is a maturity assessment on the company’s information architecture and data sources based on analytical requirements. Transactional, aggregated, and operational information is scored for quality, and the existing infrastructure’s ability to support new sources and data feed is evaluated.The time required to acquire, clean, and analyze new data is evaluated and built into the adjustment period. Businesses with multiple systems and large stores of data often struggle with duplicate data, out-of-date records, junk data, including falsified, or unverified content and missing information. Rainmaker BA can implement approaches that ensure data quality that includes processes such as de-duplication, refreshment, synchronization, cleansing, enrichment.

Understanding the nature of data available and the method of data capture is important. It is simple to identify, extract and leverage the data that resides in structured systems, such as databases and ERP, CRM and SCM applications. However, to parse unstructured content and then turn it into usable information—especially in an automated environment is challenging. In current times, the bulk of the information of companies is present in business documents, emails, social media texts/images – data that is unstructured. The challenge is to capture, catalog and prepare this data for use by analytical models to unlock valuable information that can drive productivity, shrink cycle times, improve decision making and boost the bottom line. Periodic audits of the data capture process are also important to evaluate its fit with the operational process. This will ensure that the right information is identified, extracted, and then delivered to applications as needed.