8/1/2022 - technology-and-innovation

All you need to know about analytical date

By sebastian musso

All you need to know about analytical date

Before we tackle the issue, we need to know what it is and the importance it has in the financial sector:

What is the analytical date?

The analytical date is the use of the mathematical and statistical instrument for information analysis. With it we will be able to:

  1. Ask or find the right question.
  2. Answer that question and draw conclusions.
  3. Create representative templates.
  4. Make decisions.
Currently there is an incredible, and even obscene, amount of data for use in finance. Not only are the most common ones like financial balances (i.e., cash flow, patrimonial status, etc.) that are complex not only to use, but also to compare companies from different regions. Without the use of technology it provides us with very valuable consumer information to create mathematical models that allow us to solve the four points previously named.

How to use it responsibly?

Using these data responsibly (there is therefore what happens between Google and the European Union for the use of European consumer data) created industries within the technology sector that 20 years ago or the most creative or dreamer could imagine. There are two clear industries within the technology sector benefited by the use of analytical data: social networks on the one hand and e-commerce companies on the other. This has reached the evaluations of companies such as META (previously Facebook) and AMZN (Amaz Inc.) and have created a variety of Fintech that provide algorithms for more clear information.

By ende, data analysts (majority economists or software developers with statistical emphasis) who were focused in Excel as a tool to buy the accounting and financial states of companies and to see if their evaluations were correct, had to adapt to observe and analyze different metrics. That is, the same metrics cannot be used to value companies such as WML (Walmart) and TikTok or MELI (Free Market).

What are the goals?

Large financial companies and banks in the world increasingly require the use of software languages such as R, Python, JavaScript, Go (recent created by Google), and services for using SQL database, MongoDB, DynamoDB (AWS) among others. Its goal is of course: having people trained to analyze a lot of information to be prepared at the four points we named at the beginning of the article. In addition, the marked path always tends to be equal: it begins with a question (luego if it is the correct one), collects and “limpian” the data and then discusses a model for this data. The final objective is to draw conclusions from a commercial or financial point of view to establish a path and make decisions.

In short, the analytical date for the financial sector is a “MUST”. A growing need to determine where to direct resources. From start-ups (sector that grows strongly in LATAM) to large multinationals require this knowledge and experience to boost sales, reduce costs and improve internal and security controls.

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sebastian musso

sebastian musso

I am an graduate economist of the Catholic University of Uruguay specialized in software development. Skyblue Analytics Founder, software company dedicated to the analysis of the American bag in real time.

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