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Data exploration covers collection, processing, storage, and analysis. Extracting valuable insights from the collected data informs decision-making processes and enhances overall business intelligence.

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DATA

[interview] Beyond bits and bytes — insights from data science

While navigating this data-rich environment, the question arises: How can organizations harness the potential within this vast ocean of information to stay competitive and meet the dynamic needs of modern customers?
Multiple authors

Multiple authors

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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

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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

What is a large language model? LLM explained

Large language models are powerful algorithms taking the tech world by storm. Read the article to learn what they can be used for and how they work.
Tomasz Jędrośka

Tomasz Jędrośka

Thumbnail of an article about Private Slack Chatbot: an integration of corporate resources and large language models (LLMs)
DATA

Private Slack Chatbot: an integration of corporate resources and large language models (LLMs)

Ever since the debut of ChatGPT, large language models have taken the limelight. Their breadth of knowledge is nothing short of remarkable. From drafting emails on our behalf to assisting in code development, these models showcase extensive general knowledge. Yet, a notable limitation is their unfamiliarity with specific details related to our companies, such as sensitive documents, company policies, and the like. The idea of interacting with our personal documents through such models is undoubtedly intriguing.
Katarzyna Hewelt

Katarzyna Hewelt

Thumbnail of an article about [interview] Unlocking the future: A glimpse into the world of R&D at CodiLime
DATA
NETWORKS

[interview] Unlocking the future: A glimpse into the world of R&D at CodiLime

In the ever-evolving landscape of technology, research and development (R&D) plays a pivotal role in driving innovation, pushing the boundaries of knowledge, and shaping the future of industries. R&D is the heart of organizations that innovate, explore, and create, and it is the engine behind breakthroughs that change the way we live and work. In this interview, we’ll delve into the world of R&D with Paweł Parol, the leader of one of the R&D teams at CodiLime. Paweł Parol: Well, in short, R&D stands for research and development.
Multiple authors

Multiple authors

Thumbnail of an article about [interview] The modern art of data transformations — how data engineering unlocks information potential
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 Introduction to time series for machine learning
NETWORKS
DATA

Introduction to time series for machine learning

Data is becoming an integral part of everyday life. Even if we are not fully aware of it, we deal with it all the time and it affects our lives in significant ways. This blog post elaborates on a particular type of data: time series. If you want to know more and discover what problems you can solve with time series analysis, you've come to the right place. Have you ever wondered how much data is created (including newly generated, captured, copied, or consumed data) each day? Currently it is 0.33 zettabytes every day!
Mariusz Budziński

Mariusz Budziński

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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 AI and Machine Learning for Networks: natural language processing and reinforcement learning
NETWORKS
DATA

AI and Machine Learning for Networks: natural language processing and reinforcement learning

This is the third part of the series, where we focus on the next two classes of ML methods: natural language processing and reinforcement learning. Also, we outline the major challenges of applying various ideas for ML techniques to network problems. This part also summarizes all three parts of the blog post. The first part can be found here, and the second part can be found here. Natural language processing is a part of AI which allows computer programs to understand statements and words written in human language.
Tomasz Janaszka

Tomasz Janaszka

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