Petanux - From Knowledge to Market

Datenanalyse & Optimierung

What is data analysis?

Extracting the functional meanings out of the data can be one of the most valuable achievements in this data-rich business age. Most current competition factors rely on management methods and planning strategies. Having a deep sight and effective concentration on what we currently have and what we go through to be what we deserve is the only passage to countless successes. Considering that the current businesses understand the value of data and have started to collect and organize them, every expert is trying to find ways to utilize them more in practice. Contrary to the massive data we generate, only a tiny portion is analyzed and utilized for meliorations and information, and it is still not a few. These days, with the vast amount of data and limited time, finding solutions for collecting, cleaning, organizing, and extracting information for improvement are significant and crucial. Data analysis, can be applied by very complicated approaches to discover different pattern in data. There are very extended fields to explore and experiment data in science in either straightforward or a complex way. While data analysis in business is used to make decisions for improvements all over the business performance, and overall included most functional ways rather than cutting edge technology or complex.

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What is the importance of data analysis?

In this data rich age, all businesses can take advantage of analyzing the data they were generated. In these days, the advancement of different analysis methods makes it possible to provide every business improvement requirement

  • Making decisions based on facts

    Data analysis can be advantageous since it makes you make decisions based on facts, not simple observations. For instance, knowing where we can invest our money with the most revenue is great, or how to overcome critical situations before we become any problems. We can have a vast management perspective of the entire organization in all areas to extract relevant insights and take the best strategies. 

  • Decrease the expenditures

    Having a high-quality predictive analysis makes managers discover growth opportunities and plan their strategies according to the patterns they extracted from the data. It not only helps to save budgets but also can predict different scenarios at a time.

  • Target customers pleasingly

    By analyzing customers' interests, habits, and communication channels, we can identify potential customers and avoid wasting resources on targeting the wrong people or sending the wrong message. 

What Petanux deliver

Petanux as a young SME in the field of AI, made great contribution to the industrial AI and has supported many industries in automating and developing intelligent systems and solutions. There is huge gap between science and industry to make use of the scientific achievements of AI for industries. Our mission is to support industries in efficient integration of modern and next generation AI in applications. 

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Different type of data analysis

  • Descriptive analysis: as-is

    It starts by answering the question of what is currently happening. This analysis will be provided by arranging, processing, and understanding raw data from various sources. The current situation will be represented in different visualizations to understand better what is going on without giving any insight into the future. It will focus more on why something happens.

  • Exploratory analysis: Extract the data relationship

    It aims to discover the data item relationships, extract connections, and generate the hypothesis to solve a specific problem like what is doing in data mining.