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Webinar : Implementing Hyperion System 11
Co-presented by Thought-IT and Triometric, this webinar talks through the methodologies and best practices for a successful implementation ..
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Data Analysis

Thought IT is one of the most hands-on consultancies in the market. Whilst we believe that clients benefit hugely from our knowledge and experience, we do not simply guide and advise (though we do plenty of that), we roll up our sleeves and do the work. In return, it means our knowledge and experience is not simply theoretical but is quite often gained all too painfully at the coal face.

Nowhere is this more apparent than our work on data analysis, which forms a regular part of our workload. As accountants, we are comfortable working with numbers. Our systems skills combine to give us a unique advantage in helping clients.

The work we consider under this heading includes:

  • Data reconciliation in 'problem' situations. For example, with disparate system, or where two companies have merged with incompatible reporting information.
  • Data cleansing, which often comes hand-in-hand with reconciliation. In this case it is analysing data specifically where the source is incomplete or of known poor quality. Part of the work is to identify weakness and inconsistencies, and then to provide a workable solution.
  • Data migration, which again can have elements of reconciliation and cleansing. Generally, this is likely to be part of a system implementation, where data from the legacy system needs to be pulled into a new application that does not match.
  • Data mapping. This is a specific area of work where we need to map differing level of detail between two or more systems (be it account line detail, hierarchy differences, or possible some other data dimension). This is usually required for tasks such as reporting and for extracting and loading data between systems.
  • Data automation. Given our extensive work with data, and our knowledge of automation tools, it is perhaps evident that we get called in regularly to help companies automate data flows. Some recent examples of this are: pre-populating input packs for reporting sites, taking data from ERP and ledger systems into reporting systems, and automating the production of management accounts by automating data loads into Excel.