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Advanced Data Analytics


Existing Data Analytics can be viewed as a journey through an organisation's data lifecycle involving their Transactional , Data Warehouse and Corporate Reporting systems and then we move into the completely different realm of 3Sights " Advanced Data Analytics".

Transactional Systems

These systems are used to capture and process the detailed data associated with the operational business processes (sales, service visits, accounts, etc.) and usually:

  • are used by many people each writing small amounts of data;
  • are optimised for correct data entry through system constraints;
  • are efficient (often by using complex normalised non replicated data schema);
  • can generate large volumes of detailed data;
  • are siloed with reporting specific to the requirements of the particular business process.

Data Warehouse

Data warehouses have been introduced to span across the Transactional systems to provide corporate level reporting using rationalised data where say a Customer in one system is equated to an Account in another.

This rationalisation is undertaken by some form of Extract, Transform and Load (ETL) process for each Transactional system where rules are introduced to describe exactly how to say equate that Customer to an Account and what to do if the rules are broken.

Data lifecycle

Corporate Reporting and Associated Problems

Dashboards and user capable reporting tools are then applied to the Warehouse to provide the Corporate level reporting.

Having spent millions on the resources to build, implement, maintain and use these valuable treasuries of potential insight, most organisations were pleased to obtain the detailed and heuristic information generated.

However, whilst it is possible to see that revenue had gone up by 11% last month (hindsight), it is not possible to understand why (insight) and because we do not know what we do not know, data warehouses are of limited help in providing this insight, let alone foresight where we need to model what might happen.

In addition to these intellectual challenges, the practical ETL processes (and hence the Data Warehouse) are extremely vulnerable to the Transactional data changes that occur as new or amended systems are introduced to cope with the inevitable Corporate Change pressures. The result is that over time, the ETL processes becomes more complex, onerous and expensive to maintain.

The 3Sights Advanced Data Analytics approach

To address these serious problems, 3Sights uses Advanced Data Analytics to approach this lifecycle from an entirely different perspective.

By default, the Transactional systems stay in place.

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