Data preparation covers a wide range of tasks which should precede processing and analysis. The aim of data preparation is to ensure that any tasks regarding the quality, availability, accessibility, usability, accuracy, validity, format, integrity & value of relevant, critical data (and its metadata) is conducted prior to data processing, and meets business needs. Downstream data issues attract cost, waste effort and can cripple a business.
Data preparation that enables an organisation to answer the 'what, when, when by, where, where from, where to, why, who, who by, who for, how, how long for' questions about data. As Benjamin Franklin said: "by failing to prepare, you are preparing to fail!"
Use our data sitrep to assess your data domain against stated business’ objectives, identify areas of potential risk & reward and mitigate the impact of nasty surprises.
Discovering data sounds routine but organisations are unaware of and do not 'understand' approximately 80% of their data . How much of your data swamp do you actually use, need or understand? Is it time to 'discover' your data?
Duplicate or incomplete entries; poor or missing metadata; and parsing inconsistencies are common symptoms of data quality issues. What is the opportunity cost of their adverse impact on the business and its systems?
Transformative processes such as converting, harmonising, aggregating, integrating or synchronising data; or dataset harmonisation should precede data processing for optimal performance. Is your data processing optimised?
Is your decision-making supported by reliable, valid, trusted and available data within the required timeframe. If your data, its availability and timeframe are not validated, how confident is your decision-making?