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Blog
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Confirmation Bias in Data Analysis
Confirmation bias in data analysis is the tendency for individuals to interpret data in ways that confirm their preexisting beliefs or hypotheses while disregarding or downplaying contradictory evidence. This...
Optimizing Technological Processes of a Steel Mill
Megaladata's pilot project at a major steel mill. The project confirmed the possibility of processing large amounts of data and building a quality model for heavy industry using the low-code Megaladata platform....
How to Predict Sales Using the ARIMAX Algorithm
In time series analysis, Autoregressive Integrated Moving Average (ARIMA) models are used for short-term forecasting based on past values. In this article, we will analyze the ARIMA model built in...
Data Breach 101: A Beginner's Guide
In today's digital world, our personal information is constantly being collected and stored. From online shopping to social media, we leave a trail of data wherever we go. But what happens when this...
Enterprise Information Ecosystem
In today's digitally driven business landscape, data has become an indispensable asset. The ability to effectively harness and utilize information is a key determinant of a company's success. To remain...
Sampling Methods and Algorithms in Data Analysis: Nonprobability Sampling
In our previous article, we discussed probability sampling, a method where samples are selected randomly, giving each population member an equal chance of inclusion. This article will explore...
Sampling Methods and Algorithms in Data Analysis: Probability Sampling
Sampling is a fundamental process in data analysis. It involves selecting a subset of individuals from a larger population to study. By analyzing this sample, researchers can draw reliable conclusions about...
Release notes 7.2.3
Fixed: Memory leaks in Calculator, bugs related to connections, database exports, and multiple text file imports. Improved: Operation of Neural Net, Supernode, Loop, and other components.
Improving Employee Skills in Data Science
The world is awash in data, yet we struggle to fully capitalize on its potential due to a severe shortage of skilled professionals. A significant mismatch persists between the demand for data scientists...
Working with Databases in Megaladata
Databases are one of the most popular sources of information in analytical projects. Megaladata supports work with various DBMS. This article covers all stages of work with them: connection, import, and...
ADEAL Systems and Megaladata Enter Into a Partnership Agreement
ADEAL Systems GmbH, a German vendor of IT solutions and services, and Megaladata, LLC, a data analysis solutions developer, have signed a partnership agreement.
Working with Date and Time in Calculator
The Calculator is one of the most popular components of the Megaladata platform. Let's look at examples of practical use of the Date/Time functions that are implemented in it.
What's New in Megaladata 7.2.2
Fixed a memory leak in the SOAP Service Connection, fixed errors in Connections, components of the Import and Web Services group, and some others. Expanded logging.
The Value of Data in Marketing
Marketing is undergoing a revolution driven by data. Gone are the days of generic messaging. Today's empowered customers demand personalization, and businesses that harness data to understand individual needs...
Breaking into Data Science
In this article, we'll explore the rising prominence of data science. As businesses increasingly rely on data to drive informed decisions, the demand for skilled data scientists continues to grow....
Features of Working With NULL in Megaladata
Empty values in data can create serious difficulties in processing. Using the NULL value allows you to avoid the uncertainty that arises when operating with them. Let's consider how to correctly process...
Automating Repetitive Tasks: A Boost for Productivity
Popular and exciting as it is, the work of a data professional consists not only of insights and revelations, but involves plenty of routine. Thankfully, more and more tools appear to automate the tasks one...
From Data to Knowledge: There and Back Again
Among the new capabilities of the Megaladata platform, we would like to highlight the two strategies of workflow design: "upwards", from data to models, and "downwards", from models to data. This...
Demystifying Data Science Careers
In this article, we will provide an overview of three different roles and job titles associated with analytics and data science. We will first look at the evolution of the role of data scientist.
The Limitations of Spreadsheets in a Data-Driven Financial World
The Finance sector is a data behemoth, with an estimated 150 zettabytes of data to be analyzed by 2025 according to IBM.
Statistics: The Foundation of Data Science
Statistics are a powerful tool, but interpretation is key. Don't just look at the numbers – understand their meaning: uncover hidden insights from data, compare groups and make informed decisions, replicate...
Working with Tree Structures in Megaladata
A tree model is one of the common structures for storing and transferring data. Universal exchange formats, such as JSON and XML, use exact hierarchical representations of information. However, most...
Megaladata Community Edition — Analytics Available to Everyone
Data is growing at an explosive rate, but your analysis tools are lagging behind. Does this sound familiar? Excel can't handle the data volumes. Data science specialists are hard to find and expensive to...
Data-Driven Decisions Made Easy: The Megaladata and AltMacros Partnership
This strategic partnership will leverage Megaladata's advanced analytical capabilities to enhance AltMacros' pre-built solutions, delivering even faster results and deeper insights to businesses. Expect...
Megaladata - Analysis Beyond Excel Capabilities
Excel is a software product that needs no introduction. However, despite its popularity, it has several limitations that create difficulties in solving complex analytical problems. In this article, we will...
Low-Code Philosophy as a Reason for Myth Making
Is low-code development truly a viable alternative or is it just a fad? Debunking five most common myths about low-code development and software.
Solving Typical Excel Problems Using Megaladata
Excel is a software product that needs no introduction. However, despite its popularity, it has several limitations that create difficulties in solving complex analytical problems. In this article, we will...
What’s New in Megaladata 7.2
We have added a built-in Job Scheduler and a new OpenID authentication method employing Access Token. The list of data trees-related components was enhanced with the Calculator (Tree) component. Several...
Low-Code Analytics at Top Speed
The Megaladata platform employs methods that ensure high-speed processing, efficient memory use, and easy scaling. Let's take a deeper look at what enables the platform's high performance and how...
Megaladata: What's Under the Hood?
The article describes the technological basis of the low code Megaladata platform — its components, architecture, frontend and backend, functionality, and performance. We intend to answer the most...
Cohort Analysis: Why Is It Valuable?
Every entrepreneur striving for effective business management comes to ask themself a question: What is the income brought by one client?
Coding in Megaladata: Python vs. JavaScript
This article covers the technical aspects of using programming languages in Megaladata. We compare the two languages, JavaScript and Python, analyze their limitations, and provide guidance on how to use...
Shewhart Charts as a Tool to Control Business Processes
Every business experiences failures in business processes from time to time. Finding and eliminating the causes takes not only time but also money. It is crucial to perform real-time monitoring of the...
Advanced Analytics Platforms and BI Systems — What's the Difference?
Advanced analytics platforms and Business Intelligence systems employ different approaches when dealing with data. Although data analysis takes place in both cases, there are significant differences between...
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...
Release notes 7.1.2
In the Server editions, it is now possible to connect to SAP HANA through ODBC. Fixed: Megaladata Integrator, Calculator, and some data source connections. Platform performance increased, logging...
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...
Release notes 7.1.1
Fixes made to visualizers, PostgreSQL connection, and some components. Megaladata Desktop Edition performance improved.
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...
Release notes 7.1.0
In the new version, we implemented fixes for the application, including the Export group components, database connections, association rules, and other related components.