This is the continuation of forth part of Machine Learning in Capital Markets in Capital Markets. The technical indicators are intended to help identify a trend as early as possible. The result of the various technical indicators is to provide a mathematical value that is determined from the price and trading data. It also tries to incorporate information from the past into future forecasts. … [Read more...]

An American analyst coined the term customer data platform back in 2013. Since then, there are leading experts who research and explain how marketers use CDPs to address the most important marketing challenges to be able to solve. In our previous article, we have explained that Customer Data Platform (CDP) is a software platform which creates a persistent, unified customer database that can help … [Read more...]

A Customer Data Platform (CDP) is a software platform which creates a persistent, unified customer database that can help the companies to gain a meaningful 360-degree view of their customers and, above all, their satisfaction. After all, customers who have been loyal to a company for a long time represent a reliable source of sales. Some of these software may provide marketing performance … [Read more...]

This is the continuation of third part of the series. The basis of learning from data is gathering the sources of data which can generate the forecast and a methodology to be able to evaluate them. In order to be able to create stock forecasts using machine learning, the sources must first be defined with regard to the required data. For a forecast, the data should come from sources from which … [Read more...]

This part is the continuation of part II. With the help of fundamental analysis, the value of a company is assessed taking various factors into account. The fundamental analysis approach follows the assumption that the company in question has an economic value to which the associated share price adjusts in the long term. The value of the company in question is defined as the intrinsic share value. … [Read more...]

This part is the continuation of part I. Machine learning should classify the data transmitted to it as efficiently as possible and without serious deviations. Consequently, all relevant characteristics must be selected and taken into account in order to be able to classify the relevant data. There are a total of three different procedures for annexing the existing data. In contrast to the … [Read more...]

Since the first scientific treatises on the research object of artificial intelligence in the late 1950s, the topic has become increasingly relevant. AI is now used in all newer areas of technology and is continuously being developed and optimized with regard to more efficient uses in the respective areas of application. AI, as such, presents itself as a complex area that on the one hand tries to … [Read more...]

The term data integrity refers to the correctness and completeness of the information in a database, data warehouse, data mart or in such similar structure. Our previously discussed topic Data Consistency was for a narrower space. As for the databases, the contents are modified with INSERT, DELETE or UPDATE statements, which may result in the loss of integrity of the stored data in many different … [Read more...]

Data consistency is quite commonly heard both for MySQL like DBMS and big data. With the phrase "consistency", in case of database systems, we want to refer towards meeting the requirement for any given database transaction. That is, any database transaction must only change affected data in allowed ways. For example, if we were storing a number in a database, only the numerical values are … [Read more...]

Business Intelligence is a terminology which can be assigned to business informatics, which describes procedures and processes for the systematic analysis of own company. This includes the collection, evaluation and presentation of data in electronic form. The term business intelligence became popular in the early to mid-1990s. In 1958, an article by Hans Peter Luhn appeared in the IBM Journal … [Read more...]

Today, the value of data is not unknown. Data no longer just a byproduct of business activities. Rather, most of the organizations have understood that data is valuable. Knowledge Discovery in Databases was discussed to point towards unlocking the value of data. Some of the organizations may not know how to properly collect data or convert into a useful form, or a few steps ahead - to derive … [Read more...]