{"id":17124,"date":"2023-04-19T17:50:10","date_gmt":"2023-04-19T15:50:10","guid":{"rendered":"https:\/\/www.blueway.fr\/?p=17124"},"modified":"2024-07-12T11:38:28","modified_gmt":"2024-07-12T09:38:28","slug":"data-processing","status":"publish","type":"post","link":"https:\/\/www.blueway.fr\/en\/blog\/data-processing","title":{"rendered":"The importance of seeing the full picture to effectively tackle data processing"},"content":{"rendered":"\n

Data processing is frequently reduced to data cleansing and then integration, but doing so means an incomplete picture of the process is being used. To fully exploit data, the entire data lifecycle has to be considered. Carefully managing each stage in data processing, from collection to storage, and putting the right tools and methods in place at key waypoints, will improve the effectiveness, quality and therefore the usability of your data. The entire organisation, from functional units to the C-suite, will be able to gain greater value from correctly processed data.<\/p>\n\n\n\n

What exactly is data processing ?<\/h2>\n\n\n\n

Data processing refers to the operations applied to data from the point it is collected onwards, so as to make it useable and maximise its value<\/strong>. This process has to be structured and run continuously so it is not overwhelmed by the sheer volume of data collected daily.<\/p>\n\n\n\n

While data processing can include manual processing \u2013 for example a data scientist can in some instances take charge of the first phase of processing and produce documented analyses that then join the IS and its business applications \u2013 it also includes a number of automated stages. In general, data processing entails the following phases :<\/p>\n\n\n\n

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  1. Collection: data \u2013 structured or otherwise \u2013<\/a> is collected from all available sources (data lakes, data warehouses, Excel, business applications,  IoT and so on).<\/li>\n\n\n\n
  2. Pre-processing: the data is cleansed, duplicates removed and low quality data is discarded.<\/li>\n\n\n\n
  3. Data import: the data is converted into a usable format and transported to the leading IS applications.<\/li>\n\n\n\n
  4. Processing: automated solutions are used at this stage to structure and transform data for future use.<\/li>\n\n\n\n
  5. Data exploitation: once available, the data can be queried and used (by the business, BI systems, functional processes, etc.) whether for strategic decision making or quite simply as part of the organisation’s various activities.<\/li>\n\n\n\n
  6. Storage: data processing also includes the storage phase, which is important to keep data in compliance with the GDPR and archiving standards, depending on the context.<\/li>\n<\/ol>\n\n\n\n

    The profile of the data collected at the outset and its subsequent processing are both important quality factors: data will only provide added value if it is from a trustworthy source, and then properly structured during pre-processing<\/a><\/u>, on the basis of the intended end use<\/strong>.<\/p>\n\n\n\n

    \"esb-bpm<\/figure>
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    How process (BPM) and data (ESB) integration can create value for IT and business departments ?<\/p>\n\n\n\n

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    Download white paper<\/a><\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

    How to ensure effective data processing ?<\/h2>\n\n\n\n

    At the crucial integration stage, data processing brings into play solutions such as ETL (Extract Transform Load), EAI (Enterprise Application Integration) and the application bus or ESB<\/a><\/u><\/strong>.<\/p>\n\n\n\n

    But adding value to data does not depend solely on integration<\/strong>. Data transport, storage, the efforts made to structure it and improve its quality… each of these waypoints brings about changes to the data and therefore plays a major role in its usability.<\/p>\n\n\n\n

    Another essential factor in successful processing is taking all specific needs into account, including any industry-specific standards and formats, functional business requirements, and coherent data traffic management. Adapting processing to fit the business makes a real difference.<\/p>\n\n\n\n

    A number of criteria combine to meet the needs of each business:<\/p>\n\n\n\n