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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

Hosting LLMs on AWS

In this article, I will guide you step-by-step through the process of preparing the resources needed to successfully run LLMs on AWS.
Katarzyna Hewelt

Katarzyna Hewelt

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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
OPERATIONS

Unlocking the power of MLOps: revolutionizing machine learning deployment

Artificial intelligence (AI) has rapidly gained in popularity, revolutionizing numerous industries. However, despite the rapid advancements and widespread adoption of AI technologies, a significant challenge persists.
Tomasz Janaszka

Tomasz Janaszka

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DATA

How to use convolutional networks for time series classification?

In this blog post, we would like to address the topic of time series classification. This continues our consideration of the practical use of time series in the domain of networks and cloud infrastructure. In this article we focus on a use case related to distinguishing resource consumption characteristics (e.g. CPU, memory) for different workloads in a computing cluster.
Multiple authors

Multiple authors

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DATA

Self-hosted LLM: insights and practical deployment strategies

This comprehensive guide brings LLMs closer, offering a deep dive into their fundamentals and practical insights into deploying your own LLM.
Łukasz Rogalski

Łukasz Rogalski

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NETWORKS
DATA

Long-term time series forecasting: an insight into the methods

In this article, we describe the use case and reasoning for long-term traffic forecasting, next we focus on the methods we used, and discuss alternative approaches and challenges to overcome.
Mariusz Budziński

Mariusz Budziński

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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

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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

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