Developing Software for Data Processing (AI/ML, BI and Big Data)

Do you feel overwhelmed by the data volumes? Are you looking for a stable and powerful software for efficient data processing? We will store, analyse and convert big data to neat graphics for you! Whether you want to tame big data from social media for a better targeting of your marketing campaign, analyse exchange stock data to fine-tune your business strategy, or reach a new audience for your online store – we are here to discuss your requirements and suggest the best solution!

Software for data processing

With artificial intelligence (AI) and machine learning (ML), we can make work much easier for you and automate specific business processes (such as recognition of ID photos). Possibilities for the use of AI and ML are constantly expanding and we do our best to always keep up with trends. This means your app can be among the first to offer cutting-edge, ground-breaking features! Be it a new algorithm for your game, a data mining system or robotization and automation of your production – our developers are more than happy to help you choose the right solution and suggest further steps to take. Besides that, we also offer development of data processing software for business intelligence (BI) to facilitate the use of analytics services, tools for enterprise planning or apps for human resource management.

Artificial intelligence (AI/ML)

Artificial intelligence (AI) refers to systems designed to solve complex tasks in various areas – from image or text processing to planning and management of processes based on big data.

Machine learning (ML) is one of the subareas of AI focused on algorithm-based learning of computer systems. The goal of the process is an efficient adaptation to the changes in the environment.

Both artificial intelligence and machine learning are widely used in a broad range of industries – from IT through medical sector, industrial production, translation tools to computer games. The most attractive use cases include apps and business tools to boost sales, reach new customers, schedule marketing campaigns and achieve an overall improvement in the provided services. The significance of analytics tools in eCommerce constantly increases and their efficient use is a fundamental pre-requisite for the ability to compete. Apps featuring elements of artificial intelligence and machine learning will help you, among other things, to optimise your ad spends, they will also give you insights into the performance of individual products or services and will tell you how well each sales channel is doing.

Big Data

As the title already implies, big data are too big to be processed using common software tools within sensible time frames. Their main characteristics can be subsumed under 3 Vs: volume, velocity and variety.

Volume refers to big chunks of data to be processed. These data are typically not structured and are characterised by what is known as “low density”. Processed data volumes can range from tens of terabytes to hundreds of petabytes.

Velocity means not only the velocity of the incoming data, but also of your response (processing). Big data can be first stored in a data storage; however, with certain intelligent systems, they can be assessed directly in real time.

Variety points to the multitude of data types that can be processed. Big data can also come in the form of text, audio, video or images. In and of themselves, they have no structure that would enable deriving any meaning from them. Before their processing, they need to be structured first.


Business Intelligence (BI)

Business intelligence (BI) apps are used to obtain and store data related to historical, current and future business operations, typically in a data warehouse. The goal of these apps is to provide users with analyses, insights, reports and tools for better scheduling or management. Input data are mainly figures relating to sales, production and cash flows. BI apps enable evaluation of performance both on the enterprise level and on the level of individual departments, including comparisons, predictions and other useful analyses.

The most common use of BI are analytics tools displaying the so-called business information. These tools receive data from one or more enterprise or business systems and evaluate them according to their nature.  Analytics tools offer statistics features, including statistics software packages, but also sophisticated data mining tools or predictive modelling functionalities.

Unlike BI tools, analytics services are more interpretative. Instead of merely generating reports, they also suggest possible explanations of why the given results occur, how can issues be fixed and what results can be expected in future. Some of the best-known analytics services are Google Analytics or Trustpilot.

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