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Release notes 7.1.4
Fixed: critical error in Calculator, Megaladata Integrator issues, visual problems in the workflow area. Package installation optimized.
Missing data imputation
Missing data is a very common issue in real-world data processing. The reasons may vary — data entry errors, information hiding, fraud and so on. In this article, we discuss cases where incorrect handling of...
Data leakage in machine learning
In machine learning, data leakage refers to a situation where one or more input features used during the model's learning process become unavailable when the model is applied in practice. Data leakage...
Theory of constraints: how to expand bottlenecks in data analysis
When implementing analytical projects, it is not too efficient to try to improve the system as a whole. Let’s take a look at the theory of constraints to see how low code development helps reduce the...
The Apriori algorithm for association rule learning
Apriori is one of the most popular algorithms for determining association rules. Employing the property of anti-monotonicity, Apriory is able to process large volumes of data within a reasonable amount of...
Data quality criteria
Data quality is a generalized concept that describes the degree to which information is suitable for analysis. There are a number of criteria used to assess the correctness, completeness, accuracy and...
Scalable CLOPE algorithm for clustering categorical data
Splitting of categorical and transactional data arrays into groups with similar attributes is the most important task of data mining. In most cases, traditional clustering algorithms are not effective when...
Smart sales analysis for wiser business management
The combined use of ABC and XYZ analysis will help you to better navigate the product range, optimize logistics and warehouse stocks, segment customers and partners, and properly set up interactions. ...
Implementing a decision support system: A case of one financial organization
How to migrate to a modern analytical platform and replace the database without stopping the work of the decision making pipeline. An actual case of a leader of the microfinance market.
Clustering algorithms in data mining
This article is an attempt to systematize the latest achievements in the development of data clustering techniques. The purpose of this article is not to providea detailed description of all clustering...
Genetic algorithms as a mathematical apparatus
Genetic algorithms aim to solve optimization and modeling tasks by iterating, variation and combining target parameters with the help of mechanisms similar to biological evolution.
Customer segmentation by loyalty or RFM analysis
Every entrepreneur in the process of business development is faced with the question: how to make his client more loyal and not let him go to a competitor.
Release notes 7.0.1
Errors in Megaladata Integrator, import from file sources, Replace node and operation of other handlers were corrected. Changes were introduced into BatchLauncher utilities operation. Performance of...
How to clean data before uploading it to a storage
When you create a data warehouse is not enough attention is paid to cleaning the incoming information into it. Apparently, it is believed that the larger the storage, the better. This is a surefire way to...
Detection and correction of one-dimensional outliers in data
Many analysts face the need to process outliers when it comes to data. Thankfully, Megaladata has a built-in component for quickly determining extreme values with the ability to automatically delete or...
Release notes 7.0.0
Many corrections were made in the components connected with databases and web services operation. Operation of some components was improved.
Building customers' loyalty
What is customer loyalty? Is it repeated purchases? Or an emotional connection that is manifested, for example, in the fact that the client recommends your company to their friends?