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Data engineering focuses on data architecture, data ingestion, data transformation, and data integration to ensure that data is accessible, reliable, and ready for analysis.

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DATA

Normalization vs. Denormalization in databases

Databases are like the digital brains behind many of the apps and websites we use every day. Dive into two key techniques used to organize databases: normalization and denormalization.
Arkadiusz Kordos

Arkadiusz Kordos

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DATA

What is data pipeline architecture? Definition and overview

Data pipelines are crucial in our data-driven world because they automate the flow of information, making it easier for businesses and organizations to make informed decisions, detect trends, and provide better services.
Arkadiusz Kordos

Arkadiusz Kordos

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DATA

Data cleaning techniques: Strategies for reliable data analysis

Data cleaning is a critical component of data analysis, essential for ensuring the accuracy and reliability of the results. This process involves refining data by fixing or removing errors and inconsistencies, a key step for maintaining the integrity of data-driven insights. However, this task presents various challenges. Analysts often face issues like missing values, which can lead to biased outcomes, outliers that may distort the analysis, and irregularities in data formats. If these issues are not properly addressed, they can significantly diminish the effectiveness of data analysis. Therefore, data cleaning is not merely a preliminary step; it is an integral part of producing trustworthy and actionable data insights.
Katarzyna Hewelt

Katarzyna Hewelt

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DATA

Effective cloud-based data management

Cloud data management is how organizations handle big data. Learn about the benefits and challenges of storing and processing data in the cloud.
Tomasz Jędrośka

Tomasz Jędrośka

Thumbnail of an article about What is a cloud data lake? Definition and use cases
CLOUD
DATA

What is a cloud data lake? Definition and use cases

Cloud data lakes are efficient and scalable data storage systems using the power of cloud computing. Discover their benefits and use cases in our article.
Karolina Rusinowicz

Karolina Rusinowicz

Thumbnail of an article about Understanding big data infrastructure: essentials and challenges
DATA

Understanding big data infrastructure: essentials and challenges

In today's data-driven world, organizations are gathering vast amounts of information at an unprecedented rate. This phenomenon has led to the birth and rapid evolution of "big data", a term that describes data sets so large and complex that they cannot be processed using traditional data management tools
Katarzyna Hewelt

Katarzyna Hewelt

Thumbnail of an article about Cloud-based ETL and data integration tools
DATA

Cloud-based ETL and data integration tools

Modern organizations are constantly seeking innovative solutions to streamline their data processes, and cloud-based ETL (extract, transform, load) tools can help with achieving that goal.
Tomasz Jędrośka

Tomasz Jędrośka

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DATA

[interview] The modern art of data transformations — how data engineering unlocks information potential

By 2025, global data creation is said to exceed 180 zettabytes. In 2020, we had already consumed and created more than 64 zettabytes. These data carry information that can put any business ahead of its competition. But how to take advantage of data effectively and use it to improve products, services and meet modern customers' needs? In this interview, we'll discuss the importance of data engineering with Tomasz Jędrośka, Head of Data Engineering at CodiLime. Tomasz's role is to grow this relatively new division of the company and make sure it delivers competence synergies with our Networking, Cloud, and Security services and therefore extend further CodiLime’s competitive advantages.
Multiple authors

Multiple authors

Thumbnail of an article about Detecting patterns, uncovering insights: the crucial role of data monitoring
DATA

Detecting patterns, uncovering insights: the crucial role of data monitoring

In our digital era, data is a crucial resource for a wide range of industries. The ability to manage, interpret, and derive insights from the overwhelming flood of information is essential. This is where the role of data monitoring becomes significant - a process that oversees and reviews data to ensure its quality, assess system performance, and guarantee data security. Data monitoring is a well-structured method that provides a comprehensive understanding of the state and flow of data throughout its life cycle.
Katarzyna Hewelt

Katarzyna Hewelt

Thumbnail of an article about Data wrangling — what it is and why it is important
DATA

Data wrangling — what it is and why it is important

As data continues to grow in both size and complexity, it is becoming increasingly difficult for organizations to extract valuable insights from it. This is where data wrangling comes in. Data wrangling, which is also known as data munging or data cleaning, is the process of gathering, cleaning, transforming, and preparing unprocessed data into a format that is more easily understood and analyzed. Data wrangling enables organizations to leverage the full potential of their data. In this article, we delve into data wrangling, exploring what it is, why it is important and the key tasks involved in the process.
Katarzyna Hewelt

Katarzyna Hewelt

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