Start Data Engineering
JUNE 14, 2024
1. Introduction 2. Run Data Pipelines 2.1. Run on codespaces 2.2. Run locally 3. Projects 3.1. Projects from least to most complex 3.2. Batch pipelines 3.3. Stream pipelines 3.4. Event-driven pipelines 3.5. LLM RAG pipelines 4. Conclusion 1. Introduction Whether you are new to data engineering or have been in the data field for a few years, one of the most challenging parts of learning new frameworks is setting them up!
KDnuggets
JUNE 14, 2024
This article aims to cover some of the Pandas functions essential for data analysis. You can seamlessly handle missing values, remove duplicates, replace specific values, and perform several other data manipulation tasks by mastering these tools.
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Cloudera
JUNE 14, 2024
At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage. To reach that goal, more businesses are turning toward hybrid cloud infrastructure – with data on-premises, in the cloud, or both – as a means to tap into valuable data.
ArcGIS
JUNE 14, 2024
Spatial data management track at the Esri 2024 User Conference. This blog covers all the geodatabase management related sessions.
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Whether you’re creating complex dashboards or fine-tuning large language models, your data must be extracted, transformed, and loaded. ETL and ELT pipelines form the foundation of any data product, and Airflow is the open-source data orchestrator specifically designed for moving and transforming data in ETL and ELT pipelines. This eBook covers: An overview of ETL vs.
Hevo
JUNE 14, 2024
The constant increase in the data produced by modern technologies has given rise to significant challenges, such as data complexity, inconsistencies, and breaching issues. You need a structured approach to address these challenges and mitigate the risk of comprising sensitive data. What is Data Governance in Snowflake?
Hevo
JUNE 14, 2024
Snowflake is a cloud-based platform that manages large data workloads in virtual warehouses. It is known for its unique architecture and pricing model. Snowflake charges you for the compute resources, storage, and data transfer services you utilize.
Data Engineering Digest brings together the best content for data engineering professionals from the widest variety of industry thought leaders.
Hevo
JUNE 14, 2024
Your organization might store sensitive data such as identification numbers, date of birth, or account numbers in Snowflake data warehouse tables. To ensure this information is accessible only to authorized people with appropriate roles, Snowflake supports column-level security through dynamic data masking policies.
Hevo
JUNE 14, 2024
Snowflake is a cloud data warehousing solution that has become popular for companies with large data volumes. However, moving databases from an existing data platform to Snowflake can be complicated. You may face challenges in adapting existing pipelines that require custom code or integrating data from legacy systems to Snowflake’s environment.
Hevo
JUNE 14, 2024
How do you visualize your Snowflake data? Snowsight, the visual interface of Snowflake, allows two different easy ways to visualize your data within Snowflake- by using charts or dashboards.
Hevo
JUNE 14, 2024
Schema management is crucial for ensuring data quality and consistency in a database. One prominent feature it enables is version control and change management. Version control helps maintain the history of schema versions, allowing an efficient way to track the changes made to the schema.
Speaker: Tamara Fingerlin, Developer Advocate
In this new webinar, Tamara Fingerlin, Developer Advocate, will walk you through many Airflow best practices and advanced features that can help you make your pipelines more manageable, adaptive, and robust. She'll focus on how to write best-in-class Airflow DAGs using the latest Airflow features like dynamic task mapping and data-driven scheduling!
Hevo
JUNE 14, 2024
Organizations often struggle with data silos and inconsistencies due to customer data being dispersed across multiple systems. Such scattered data can hinder the ability to make informed, data-driven decisions. Platforms like Salesforce and Snowflake help address these challenges by unifying customer data and robust analytics.
Hevo
JUNE 14, 2024
Azure Data Factory (ADF) is a Microsoft-managed data integration solution that facilitates the creation of cloud-based data workflows. It is a fully managed service that can be used to build data pipelines by orchestrating data movement. Snowflake is a fully managed SaaS (Software-as-a-Service) tool that offers cloud-based data warehouse services.
Hevo
JUNE 14, 2024
Different systems and databases use various date formats. Converting date data into a consistent format will ensure accuracy across systems. For instance, you are collecting sales data from other regions that use different formats. Combining and analyzing the sales data would be time-consuming and error-prone if the data is not standardized.
Hevo
JUNE 14, 2024
Data analytics helps to derive valuable insights from your raw data. It helps you align your business processes for better outcomes by identifying trends and patterns in the data that would otherwise be lost.
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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
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