Big Data technologies give access to qualitatively fresh knowledge and opportunities that not just afford firms a competitive edge on the market. Hire big data developers is a good way to run this process.
The industry spectrum of big data apps is very wide. Let’s look at the most obvious uses of these technologies.
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Retail trade
Large retail chains that accumulated significant volumes of data can provide a lot of useful analytical info for top managers:
- what products are in demand,
- whether there is enough of them in the warehouse,
- whether the supplies are well organized,
- which stores are the most profitable.
For analytics, tools such as SAP HANA are used. It allows a supermarket with more than 10 thousand items to spend just 5 minutes receiving detailed info on them instead of 15 days as in manual analysis.
Metallurgy
The share of energy resources in the expenses of metallurgical enterprises has increased to 30%. That’s why the topic of energy-saving management is becoming more and more topical, and today it is the responsibility of general directors and chief engineers. Often they do not have complete information about energy consumption. In the metallurgical industry, big data is valuable for studying sales strategies and price policy formation.
Financial industry
In financial organizations, SAP HANA can serve both as an electronic trading floor and as a tool for analyzing creditworthiness or calculating capital adequacy ratios. For banks, big data can be useful for credit scoring as well as underwriting – modeling the scenario of passing the application of the borrower in which deviations from credit rules are recorded and the credit limit is calculated.
Oil and gas industry
Big data in the oil and gas industry is used both when extracting resources and when marketing them. In production, of course, it is important to assess the efficiency of field development. It implies a huge set of functions:
– comprehensive analysis and identification of sub-optimal development sites,
– targeted planning of measures, selection of geological and technical measures, forecast of effects,
– selection of optimal options of measures programs,
– development modes in accordance with production, economic and infrastructural constraints.
Telecom
Advanced big data technologies are used in telecommunications as well. One of its apps is subscriber loyalty management. Companies use big data and data science consulting to build subscriber profiles:
- they segment the customer base,
- evaluate preferences,
- calculate profitability for each group.
Then they analyze customer call records for dozens and hundreds of customizable parameters and determine subscriber social groups. This is followed by planning and pre-assessment of marketing campaigns and qualitative targeting based on subscriber profiles. As a result, marketing helps prevent subscriber churn by identifying and evaluating the significance of factors that influence loyalty.
Transportation
There is an interesting solution for controlling dislocation and schedule execution and schedule planning on the railroad. Firstly, it provides an analysis of train traffic deviations with the reasons for delays. And secondly, it enables flexible and fast processing of customer requests by quickly calculating different options of order execution (for example, offering other terms or another volume, at more favorable prices for the customer) with optimality criteria of schedule fulfillment, company profit, and customer satisfaction. Big data can also improve accounting for diesel fuel consumption.
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