Areas_of_application
Examples of applications
Examples of applications within industries
Business reports and analysis
Data mining and dredging
Data warehouses
Big Data and stream processing
Manufacturing companies
Retail sales
Transport, shipping, logistics
FMCG
Finance
Motorisation
Health service
E-commerce
Media and entertainment
Travel and tourism
Telecommunications and IT
  • analytical reports
  • process monitoring
  • corporate reports
  • reports built ad-hoc
  • management panels
  • data exports to external formats: PPTX, PDF, Excel, etc.

The data mining process relies on data selection, compilation and analysis.

Some examples of the opportunities from data mining for the company:

 

  • How can we optimise the production costs?
  • What is the product availability status over time?
  • What is demand planning on the basis of WFA/Attainment indicators?
  • What is the expected return on planned investments next year?
  • Which clients are most promising and which may move to the competition?
  • How can a company loyalty programme be strengthened?
  • Can potential fraud be detected?

This kind of engine allows ultra-fast searches and analyses all your content efficiently, meaning that ownership results in numerous benefits:

 

  • consistency in information – all data stored in the warehouse has one common form
  • elimination of errors – before the data is loaded into the warehouse, all possible inconsistencies are identified and levelled out – the reporting and analysis process is significantly improved

  • We primarily associate Big Data as datasets with a significant amount of data, speed of processing and diversity in the data.

  • When it comes to Big Data, we typically process large amounts of unstructured data. For some companies, this can be several dozen terabytes of data (e.g. corporate/corporate department level). For others, this may involve hundreds of petabytes (e.g. group entity level).

  • Speed means receiving and processing data from sources at high frequency and using it for presentation in an appropriate structure. Some smart devices with internet access operate in real or near-real time, and require real-time assessment and action. For example, IoT allows a company to monitor shipments in real time and incorporate data on route conditions into decisions that can save a lot of time and money.

  • Diversity means handling many types of data. With the development of Big Data, new and unstructured types of data have begun to be collected. Unstructured and semi-structured data types, such as text, audio and video, require additional pre-processing to bring out their business relevance.
  • Stream processing is a big data technology that focuses on the real-time processing of continuous streams of variable data – providing immediate results from their analysis. 
  • Benefits include immediate detection of conditions and anomalies in a very short time, which is useful for tasks such as early fraud detection.
  • Streaming data processing systems in Big Data are effective solutions when we have operating scenarios that require: minimal latency, built-in features to handle imperfect data, SQL queries on data streams to build extended operators, guaranteed ability to generate predictable and repeatable results, stored and streamed data integration abilities, fault tolerance features, guaranteed data security and availability, real-time response ability with minimal load for high-volume data streams and the ability to automatically scale applications between multiple processors and nodes.
  • Analysis of production by product
  • Analysis of production by period
  • Analysis of production by use of a specific material
  • Periodic reports
  • Cyclical reports
  • Material consumption reports
  • Analysis of sales based on specific merchandise by code
  • Sales analysis based on the use of a loyalty card
  • Sales analysis based on a specific promotional action
  • Sales analysis based on the promotion period
  • Sales reports
  • Merchant report (price differences of ordered products over time)
  • Report on parts for selected cars or a specific car
  • Reports on average routes,
  • Combustion report for a specific vehicle or group of vehicles
  • Analysis of vehicle absorption by period or specific time period
  • Contractor report
  • Route profitability report
  • Report on average profit per kilometre per contractor
  • Report on average profit of orders from a specific country
  • Analysis of sales based on specific merchandise by code
  • Promotion period report
  • Loyalty card usage report on purchases
  • Weekly, monthly and annual reports, 
  • Overall turnover reports for a shop or group of shops
  • Merchant report (price differences of ordered products over time)
  • Non-rotating goods report
  • Analysis of the average client basket
  • Periodic financial reports
  • Accounting reports
  • Market analysis including specific markers
  • Financial analysis of the organisation
  • Credit reports
  • Popularity of the chosen financial/credit programme
  • Analysis of the occurrence of credit collection in a given period of time
  • Reporting of the most frequent defect rates by season
  • Analysis of the utilisation rate of operational components
  • Reporting of periodic sales or a specific time period
  • Sales report for a particular service
  • Sales report for a specific model/part
  • Analysis of the occurrence of the most common diseases, along with a report
  • Patient density report for the period in question
  • Report on prescribing of specific medicines
  • Analysis of patients' course of treatment (by drug/therapy)
  • Patient base with their annual density of attendance at healthcare facilities
  • Analysis of the patient's outcomes against the treatment method and report on any improvement or deterioration in the patient's health
  • Analysis of sales based on specific merchandise by code
  • Analysis based on the promotion period
  • Analysis based on the season of the year
  • Sales reports
  • Goods turnover reports
  • Goods popularity reports
  • Attendance report (on the page in a specific section)
  • Report on non-returning goods
  • Analysis of the average client basket
  • Merchant report (price differences of ordered products over time)
  • Viewing reports
  • Tracking popularity reports
  • Analysing visits after the work has been uploaded
  • Analysing audience traffic in relation to a specific event/season
  • Reports related to the popularity of tourism programmes
  • Seasonal popularity reports
  • Tourist traffic reports
  • Reports related to the average basket of tourist choices
  • Analysing the market advantage of tourism programmes
  • Analysing the use of selected tourism services
  • System load analysis
  • Analysis of communication bottleneck reduction at specific times of the day
  • Reports on the client's use of selected services or all services
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