Jesse Anderson

FEBRUARY 11, 2025

Discover the insights he gained from academia and industry, his perspective on the future of data processing and the story behind building a next-generation graph database. Semih explains how Kuzu addresses the challenges of large graph analytics, the benefits of embeddability, and its potential for applications in AI and beyond.

Computer Science 130

Computer Science Database Design Software Engineer Software Engineering 130

ProjectPro

JUNE 6, 2025

Looking for an efficient tool for streamlining and automating your data processing workflows? Let's consider an example of a data processing pipeline that involves ingesting data from various sources, cleaning it, and then performing analysis. Airflow operators hold the data processing logic.

Data Pipeline 63

Data Pipeline PostgreSQL Python Database 63

Start Data Engineering

MAY 28, 2024

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Use DuckDB 4.4.

Data Pipeline 219

Data Pipeline Python Building Data 219

Snowflake

JUNE 10, 2025

Dynamic Tables updates Dynamic Tables provides a declarative processing framework for batch and streaming pipelines. This approach simplifies pipeline configuration, offering automatic orchestration and continuous, incremental data processing.

Data Pipeline 83

Data Pipeline SQL Python Building 83

ProjectPro

JUNE 6, 2025

Data Ingestion Data Processing Data Splitting Model Training Model Evaluation Model Deployment Monitoring Model Performance Machine Learning Pipeline Tools Machine Learning Pipeline Deployment on Different Platforms FAQs What tools exist for managing data science and machine learning pipelines?

Machine Learning 58

Machine Learning Building Amazon Web Services Deep Learning 58

ProjectPro

JUNE 6, 2025

But, before we delve into the specifics of these tools, let's establish a foundational understanding of what a data pipeline is and why it is indispensable in data analytics and business intelligence. What are Data Pipelines? Pros Messages are replicated across multiple brokers for durability. Built to be highly fault-tolerant.

Data Pipeline 49

Data Pipeline Google Cloud Kafka AWS 49

Cloudera

DECEMBER 2, 2024

Cloudera is committed to providing the most optimal architecture for data processing, advanced analytics, and AI while advancing our customers’ cloud journeys. Together, Cloudera and AWS empower businesses to optimize performance for data processing, analytics, and AI while minimizing their resource consumption and carbon footprint.

AWS 89

AWS Amazon Web Services Cloud Computing Utilities 89

ProjectPro

JUNE 6, 2025

Data engineering is the foundation for data science and analytics by integrating in-depth knowledge of data technology, reliable data governance and security, and a solid grasp of data processing. Data engineers need to meet various requirements to build data pipelines.

AWS 52

AWS Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 6, 2025

With the global data volume projected to surge from 120 zettabytes in 2023 to 181 zettabytes by 2025, PySpark's popularity is soaring as it is an essential tool for efficient large scale data processing and analyzing vast datasets. They are distributed across the cluster, enabling efficient data processing at scale.

Hadoop 68

Hadoop Metadata Java Datasets 68

Snowflake

MARCH 26, 2025

In this edition, we talk to Richard Meng, co-founder and CEO of ROE AI , a startup that empowers data teams to extract insights from unstructured, multimodal data including documents, images and web pages using familiar SQL queries. What inspires you as a founder?

Unstructured Data 98

Unstructured Data SQL Data Workflow Data 98

ProjectPro

JUNE 6, 2025

To do that, they must use data visualization tools such as Microsoft Power BI , Tableau , etc., to create visualizations that narrate the characteristics of the data at hand. Real-time data processing frameworks are used to process data streams and handle data as it is generated. PREVIOUS NEXT <

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Master PySpark RDD operations and concepts with our concise and comprehensive PySpark cheat sheet, empowering you to unlock the potential of distributed data processing. Resilient Distributed Datasets (RDDs) are a fundamental abstraction in PySpark, designed to handle distributed data processing tasks.

Datasets 40

Datasets Algorithm Utilities Big Data 40

ProjectPro

JUNE 6, 2025

Snowflake Data Marketplace gives users rapid access to various third-party data sources. Moreover, numerous sources offer unique third-party data that is instantly accessible when needed. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 56

Architecture IT Data Warehouse Amazon Web Services 56

ProjectPro

JUNE 6, 2025

Consider a data processing function that requires significant memory resources. Suppose an analytics application experiences a cold start or intermittent delays in processing data. In-depth log analysis reveals spikes in cold starts during specific data processing tasks, guiding developers to optimize those functions.

AWS 58

AWS Amazon Web Services Programming Language Media 58

Snowflake

MAY 8, 2025

Note: The Egress Cost Optimizer cache uses third-party subprocessors that adhere to the Snowflake data processing addendum. You can find complete information here about the region in which your data is processed by our subprocessor. Accounts can always disable ECO by going to Snowflake Provider Studio Settings.

AWS 70

AWS Cloud Algorithm Data Security 70

Snowflake

MARCH 20, 2025

When they deploy Contextual AI as a Snowflake Native App , they get the peace of mind that comes with running the platform and the data processing inside their own Snowflake environment, while Snowflake manages the infrastructure complexity, including server management, scaling and maintenance.

Certification 95

Certification Programming Designing Building 95

Cloudera

DECEMBER 4, 2024

For example: An AWS customer using Cloudera for hybrid workloads can now extend analytics workflows to Snowflake, gaining deeper insights without moving data across infrastructures. Or now customers can combine Cloudera’s raw data processing and Snowflake’s analytical capabilities to build efficient AI/ML pipelines.

AWS 89

AWS Raw Data Relational Database Government 89

ProjectPro

JUNE 6, 2025

Apache Spark has become a cornerstone technology in the world of big data and analytics. Learning Spark opens up a world of opportunities in data processing, machine learning, and more. Familiarize yourself with concepts like distributed computing, data storage, and data processing frameworks.

Programming Language 40

Programming Language Scala Hadoop Java 40

ProjectPro

JUNE 6, 2025

Skills Developed : Real-time data processing with Kafka Building anomaly detection workflows Real-time visualization with Grafana 7) Weather Pattern Prediction Industries like agriculture, logistics, and disaster management need accurate weather predictions to reduce risks and improve operational planning.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ProjectPro

JUNE 6, 2025

Get ready to supercharge your data processing capabilities with Python Ray! ​​Imagine you're a data scientist working with massive amounts of data, and you need to train complex machine learning models that can take days or even weeks to complete. This is where Python Ray comes in.

Python 45

Python Datasets Machine Learning Data Science 45

ProjectPro

JUNE 6, 2025

In response to these challenges, Google has evolved its previous batch processing and streaming systems - including MapReduce, MillWheel, and FlumeJava - into GCP Dataflow. This new programming model allows users to carefully balance their data processing pipelines' correctness, latency, and cost.

Google Cloud 40

Google Cloud Java Data Ingestion SQL 40

Snowflake

NOVEMBER 19, 2024

To overcome these hurdles, CTC moved its processing off of managed Spark and onto Snowflake, where it had already built its data foundation. Thanks to the reduction in costs, CTC now maximizes data to further innovate and increase its market-making capabilities.

Data Governance 98

Data Governance Government Healthcare Management 98

The Pragmatic Engineer

MARCH 19, 2024

A 1959 survey had found that in any data processing installation, the programming cost US$800,000 on average and that translating programs to run on new hardware would cost $600,000. From Wikipedia : “In the late 1950s, computer users and manufacturers were becoming concerned about the rising cost of programming.

Software Engineer 331

Software Engineer Software Engineering Programming Language Media 331

Edureka

APRIL 22, 2025

AI-powered data engineering solutions make it easier to streamline the data management process, which helps businesses find useful insights with little to no manual work. Real-time data processing has emerged The demand for real-time data handling is expected to increase significantly in the coming years.

Data Engineering 52

Data Engineering Data Engineer Engineering Consulting 52

Snowflake

MARCH 19, 2025

Explore AI and unstructured data processing use cases with proven ROI: This year, retailers and brands will face intense pressure to demonstrate tangible returns on their AI investments.

Media 95

Media Retail Entertainment Unstructured Data 95

ProjectPro

JUNE 6, 2025

The Engine crafts a query plan, introduces operators and expressions for data processing, and executes queries, akin to a relay race passing the baton from one stage to another. This integration simplifies data processing tasks and extends the capabilities of Hadoop for analysts and data scientists.

Big Data 40

Big Data Architecture Project Hadoop 40

ProjectPro

JUNE 6, 2025

From the fundamentals to advanced concepts, it covers everything from a step-by-step process of creating PySpark UDFs, demonstrating their seamless integration with SQL , and practical examples to solidify your understanding. As data grows in size and complexity, so does the need for tailored data processing solutions.

SQL 40

SQL Python Big Data Metadata 40

ProjectPro

JUNE 6, 2025

Azure Databricks is a robust cloud-based analytics and data processing platform for various data-related tasks. Compute Management: Databricks allows you to manage the compute resources required for data processing tasks. This is also where data processing takes place.

Data Engineer 40

Data Engineer Data Engineering Engineering Data Lake 40

Pinterest Engineering

NOVEMBER 18, 2024

CDC allows applications to respond to these changes in real-time, making it an essential component for data integration, replication, and synchronization. Real-Time Data Processing : CDC enables real-time data processing by capturing changes as they happen. Why is CDC Important?

Kafka 59

Kafka MySQL Database Software Engineering 59

ProjectPro

JUNE 6, 2025

Unlike batch processing, which handles data in large chunks at scheduled intervals, stream processing operates on a flow of data, processing each event or transaction as it occurs. In industries where speed is critical, stream processing outshines batch processing due to its minimal latency.

Process 40

Process Kafka Hadoop Banking 40

DataKitchen

NOVEMBER 5, 2024

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. By systematically moving data through these layers, the Medallion architecture enhances the data structure in a data lakehouse environment.

Architecture 78

Architecture Raw Data Pipeline-centric Data Ingestion 78

ProjectPro

JUNE 6, 2025

What industry is big data developer in? What is a Big Data Developer? A Big Data Developer is a specialized IT professional responsible for designing, implementing, and managing large-scale data processing systems that handle vast amounts of information, often called "big data."

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

With the ability to handle streaming data ingestion rates of up to millions of events per second, Amazon Kinesis has become a popular choice for high-volume data processing applications. Ready to take your data streaming to the next level? Scalable: Amazon Kinesis provides a highly scalable platform for streaming data.

Kafka 40

Kafka AWS Amazon Web Services Data Ingestion 40

ProjectPro

JUNE 6, 2025

If someone is looking to master the art and science of constructing batch pipelines, ProjectPro has got you covered with this comprehensive tutorial that will help you learn how to build your first batch data pipeline and transform raw data into actionable insights. You can write Spark jobs in Python using libraries like PySpark.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

ProjectPro

JUNE 6, 2025

Table of Contents What is Real-Time Data Ingestion? Data Collection The first step is to collect real-time data (purchase_data) from various sources, such as sensors, IoT devices, and web applications, using data collectors or agents.

Data Ingestion 40

Data Ingestion Kafka Google Cloud AWS 40

ProjectPro

JUNE 6, 2025

Learn all about Azure ETL Tools in minutes with this quick guide, showcasing the top 7 Azure tools with their key features, pricing, and pros/cons for your data processing needs. Many are turning to Azure ETL tools for their simplicity and efficiency, offering a seamless experience for easy data extraction, transformation, and loading.

ETL Tools 40

ETL Tools Data Engineer Data Engineering Data Lake 40

ProjectPro

JUNE 6, 2025

With the rapid growth of data in the industry, businesses often deal with several challenges when handling complex processes such as data integration and analytics. This increases the demand for big data processing tools such as AWS Glue.

AWS 40

AWS IT Data Lake BI 40