HomeBIG DATABig Data Is Primarily Intended To Improve Productivity

Big Data Is Primarily Intended To Improve Productivity

The topic of big data is mostly dealt with from the point of view of the available technologies. Comparatively little is heard, about applications and users. A market research company Expert on shows that many medium-sized and large companies want to invest in big data and are hoping for a competitive advantage.

Data growth is a major challenge for companies. Of 155 companies surveyed by the market research and consulting firm Expert on Group between June and September on big data and data analysis, 29% expect data to increase. The flood of data is particularly heavy for medium-sized companies with between 500 (43%) and 999 (54%) employees.

The Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) reports that 1.8 zettabytes of data were produced worldwide. According to the forecasts of the Fraunhofer experts, the data volume will double every two years. There is still a lot of catching up to do because the topic of big data is currently heavily US-dominated.

More Than 50% Of The Companies Surveyed Are Concerned With Big Data

Over half of the companies surveyed by Expert on have already dealt with the topic of big data. Companies with up to 500 employees are behind – for them, this only applies to 26%. On the other hand, companies with more than 1000 employees are completely different: Conversely, only a quarter of them are (still) ignorant of big data.

According to Expert on, the Big Data category only includes applications or technologies that meet at least two of the following four criteria: unusually large amounts of data, unusually fast analysis, particularly high data or analysis quality, or the inclusion of an unusually large number of different data sources.

With planned or the few already implemented big data installations, users are primarily striving for more productivity, better integration of new, especially unstructured data sources, higher data quality, faster processes, and data implementation in relevant decision-making templates. The first-mentioned goal is dominant among the smaller medium-sized companies with up to 500 employees, while data quality improvement is clearly at the fore in large companies.

Big Data Is Particularly Relevant For Risk Management

According to the respondents, the new technology is particularly relevant for risk management, scoring and controlling, logistical and sales processes, pricing, competitive analysis, and the analysis of information on the web. The information generated will be used primarily by top management, the finance and controlling department, and the logistics department.

Many questions in the study related to big data and data analysis methods in general. The tools used for this task do not completely satisfy the users. Above all, the handling of unstructured data, the implementation of the technologies in the company, the report features, the data quality, and the user acceptance were criticized. “This is a clear request to the providers to improve something here.”

Currently, the respondents mainly use company reporting, ad-hoc evaluation and analysis (both of which are used by over 50%), data mining, notification services, and real-time analyzes. User interfaces, real-time analyzes, information portals, and website analyzes will likely experience strong growth shortly.

To perform these tasks, 84% of the time relational databases are used today, and their share will decrease to 74% in the future. Object-oriented databases (today: 32%, future: 44%), column-oriented database systems without processing in the main memory (today: 11%, in the future: 30%) and with processing in the main memory (today 19%, in the future: 33%) will spread . The proportion of databases based on open source (47%), on the other hand, will hardly change.

Higher Budgets For Data Analysis And Management

Anyone who carries out new projects in data analysis and management primarily wants to automate previously manual processes (81%), operate quality management (68%), get a grip on data growth (63%), or increase overall efficiency (59%). These are important goals, but the projects in question stand in the way of a lack of internal know-how (40%) or external personnel resources to bring the necessary knowledge into the company (52%). Half of the respondents complained about budget bottlenecks, 47% complained about the complex development. “It is high time to train big data analysts who are responsible for the graphical implementation of analysis results.”

Half of the respondents planned a higher budget for data analysis and management, with large companies investing the most money in the topic with an increase of 13.5%. Above all, investments in databases, special business intelligence solutions, and storage hardware are planned.

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