Big Data and IT Projects - Comparison of Their Success Rate and Complexity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F21%3A00008871" target="_blank" >RIV/46747885:24310/21:00008871 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Big Data and IT Projects - Comparison of Their Success Rate and Complexity

Popis výsledku v původním jazyce

The pressure to process data increases with its quantity. The amount of data increases exponentially every year. According to estimates, in 2020 it should reach the size of almost 59 ZB. This growth trend will undoubtedly continue in the future. The estimated amount of data generated in 2025 is 175 ZB. In addition to the amount of data, its structure has also been changing. Structured data prevailed before, but now most data is in an unstructured form, and its processing is significantly more complex. Companies have been responding to this and investing in the development and implementation of new technologies for processing diverse data, even in real time. It is Data Science that focuses on this issue, particularly on Big Data processing. However, projects focused on the implementation and development of Big Data solutions often end in failure. Are other IT projects so unsuccessful as well? Are Big Data projects more complex than other IT projects? On what aspects does the successful outcome of Big Data projects depend? The aim of this article is to answer these questions. The related research included quantitative and qualitative survey focused on experience with Big Data projects. The article compares the results of surveys focused on Big Data and common IT projects, especially in terms of their success and complexity. The survey helps to clarify some of the differences between Big Data and ordinary IT projects.

Název v anglickém jazyce

Big Data and IT Projects - Comparison of Their Success Rate and Complexity

Popis výsledku anglicky

The pressure to process data increases with its quantity. The amount of data increases exponentially every year. According to estimates, in 2020 it should reach the size of almost 59 ZB. This growth trend will undoubtedly continue in the future. The estimated amount of data generated in 2025 is 175 ZB. In addition to the amount of data, its structure has also been changing. Structured data prevailed before, but now most data is in an unstructured form, and its processing is significantly more complex. Companies have been responding to this and investing in the development and implementation of new technologies for processing diverse data, even in real time. It is Data Science that focuses on this issue, particularly on Big Data processing. However, projects focused on the implementation and development of Big Data solutions often end in failure. Are other IT projects so unsuccessful as well? Are Big Data projects more complex than other IT projects? On what aspects does the successful outcome of Big Data projects depend? The aim of this article is to answer these questions. The related research included quantitative and qualitative survey focused on experience with Big Data projects. The article compares the results of surveys focused on Big Data and common IT projects, especially in terms of their success and complexity. The survey helps to clarify some of the differences between Big Data and ordinary IT projects.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů