Christophe Blefari

APRIL 19, 2024

Structured generative AI — Oren explains how you can constraint generative algorithms to produce structured outputs (like JSON or SQL—seen as an AST). This is super interesting because it details important steps of the generative process. SQLMesh is bringing fresh ideas to the SQL transformation landscape.

MySQL 130

MySQL Data Datasets SQL 130

dbt Developer Hub

JUNE 30, 2020

When your data is small enough, this is the preferred approach, however it isn’t scalable. Because dbt is primarily designed for batch-based data processing, you should not schedule your dbt jobs to run continuously. Lambda views are a simple and readily available solution that is tool agnostic and SQL based.

SQL 52

SQL Lambda Architecture Raw Data Architecture 52

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 103

Data Engineering Data Engineer Engineering Metadata 103

Christophe Blefari

SEPTEMBER 15, 2023

💡 Additional big tech stuff to check: real-time ML training at Etsy and last mile data processing with Ray at Pinterest. Dimensional data modeling with dbt — A great 6-steps process to create a simple dim-fact model with dbt. Data Economy 💰 Databricks atm ( credits ) SQream raises $45m Series C.

Data Warehouse 130

Data Warehouse Data SQL Python 130

Knowledge Hut

APRIL 25, 2024

Big data is a term that refers to the massive volume of data that organizations generate every day. In the past, this data was too large and complex for traditional data processing tools to handle. There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.

Java 98

Java Hadoop Scala SQL 98

ProjectPro

JANUARY 20, 2016

“I want to work with big data and hadoop. ” How much SQL is required to learn Hadoop? In our previous posts, we have answered all the above questions in detail except “How much SQL is required to learn Hadoop?” Studies found that the de facto language for analysts was SQL.

Hadoop 52

Hadoop SQL Java Big Data 52

Cloudera

MARCH 2, 2023

Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables. This enables you to maximize utilization of streaming data at scale.

Process 112

Process SQL Kafka Database 112

Christophe Blefari

DECEMBER 16, 2022

For instance a small team of 2 analytics engineers will pay now $2400/year just to have a server running their SQL queries and a web IDE that is yet to perfect. Query your data in Kafka using SQL — This is a post that compares Flink, ksqlDB, Trino, Materialize, RisingWave and timeplus (the authors) in order to query Kafka.

Kafka 130

Kafka Data SQL Cloud 130

Team Data Science

DECEMBER 17, 2020

It’s not a must for data scientist to have skill in data engineering before they can analyze data processed by data engineer or before they can move uniformly with other group (involving data engineer) for the progress of the company. Data scientists should acquire some basic SQL functionality.

Data Engineering 130

Data Engineering Data Engineer Engineering Cloud Computing 130

ProjectPro

MAY 12, 2016

Since the emergence of the Hadoop ecosystem , programmers and analysts having years of experience with SQL - suddenly felt crippled with the new big data technology. They aim to put a comfortable and familiar SQL-based front end to query the vast expanse of data stored under Hadoop architecture.

Hadoop 40

Hadoop SQL Business Intelligence Java 40

Ascend.io

SEPTEMBER 5, 2023

In this article, we’ll explore what Snowflake Snowpark is, the unique functionalities it brings to the table, why it is a game-changer for developers, and how to leverage its capabilities for more streamlined and efficient data processing. SQL, as a declarative language, offers a broad audience the power to query data.

IT 59

IT Scala Java Programming Language 59

Knowledge Hut

MARCH 28, 2024

Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. Education & Skills Required Proficiency in SQL, Python, or other programming languages. Implement data ingestion, processing, and analysis pipelines for large-scale data sets.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

FreshBI

MARCH 7, 2024

Our Solution In collaboration with COFI, FreshBI implemented a comprehensive solution: Automated Data Retrieval and Processing : FreshBI developed a customized Python script to extract data from a Canadian lumber statistics API. This script efficiently cleansed and structured the data before storing it in COFI's SQL database.

BI 59

BI Manufacturing Business Intelligence Python 59

Knowledge Hut

MAY 2, 2024

As per Apache, “ Apache Spark is a unified analytics engine for large-scale data processing ” Spark is a cluster computing framework, somewhat similar to MapReduce but has a lot more capabilities, features, speed and provides APIs for developers in many languages like Scala, Python, Java and R.

Scala 52

Scala Hospitality Healthcare Retail 52

Knowledge Hut

DECEMBER 26, 2023

Certain roles like Data Scientists require a good knowledge of coding compared to other roles. Data Science also requires applying Machine Learning algorithms, which is why some knowledge of programming languages like Python, SQL, R, Java, or C/C++ is also required.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Christophe Blefari

JANUARY 20, 2024

The Rise of the Data Engineer The Downfall of the Data Engineer Functional Data Engineering — a modern paradigm for batch data processing There is a global consensus stating that you need to master a programming language (Python or Java based) and SQL in order to be self-sufficient.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

OCTOBER 16, 2023

With Cloudera Open Data Lakehouse in the private cloud, you can benefit from following key features: Multi-engine interoperability and compatibility with Apache Iceberg, including NiFi, Flink and SQL Stream Builder (SSB), Spark, and Impala. to stream ingest data sets to Iceberg. Cloudera Flow Management 2.1.6

Cloud 76

Cloud Kafka SQL Data 76

Knowledge Hut

DECEMBER 28, 2023

Competitive Advantage: Utilizing Hadoop projects can give organizations a competitive edge through data-driven insights. Diverse Data Processing: Hadoop supports various data types and complex analysis challenges. Cost-Effectiveness: Hadoop is a cost-effective solution compared to traditional data processing systems.

Hadoop 52

Hadoop Project Datasets Big Data 52

Edureka

AUGUST 2, 2023

R’s popularity in the data science community is also evident through its active community support and continuous development of new packages and techniques. SQL Structured Query Language, or SQL, is used to manage and work with relational databases. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Christophe Blefari

JANUARY 14, 2023

In the end Python and SQL are still here for good. On the data processing side there is Polars, a DataFrame library that could replace pandas. With this release you can really mix Python and SQL code. But with Rust the approach is different.

Python 130

Python Kafka Data Scala 130

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

NOVEMBER 17, 2023

Here is a step-by-step guide on how to become an Azure Data Engineer: 1. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. You ought to be able to create a data model that is performance- and scalability-optimized.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. VDK ingests data from the Data Source.

Data Lake 87

Data Lake Data SQL Data Warehouse 87

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional responsible for designing, implementing, and managing data solutions using Microsoft's Azure cloud platform. They work with various Azure services and tools to build scalable, efficient, and reliable data pipelines, data storage solutions, and data processing systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

NOVEMBER 2, 2023

These Azure data engineer projects provide a wonderful opportunity to enhance your data engineering skills, whether you are a beginner, an intermediate-level engineer, or an advanced practitioner. Who is Azure Data Engineer? CSV, SQL Server), transform it, and load it into a target storage (e.g.,

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Cloudera

JUNE 18, 2022

Warehouses are vertically integrated for SQL Analytics, whereas Lakes prioritize flexibility of analytic methods beyond SQL. As use cases matured, we saw the need for both efficient, interactive BI analytics and transactional semantics to modify data. But with vastly different architectural worldviews.

Data Lake 90

Data Lake Data Warehouse BI SQL 90

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Netflix Tech

MARCH 10, 2023

Data Reprocessing Pipeline Flow Data Extractor Cassandra is the primary data store of the asset management service. With SQL datastore, it was easy to access the existing data with pagination regardless of the data size. But there is no such concept of pagination with No-SQL datastores like Cassandra.

Management 94

Management Kafka Metadata Media 94

Start Data Engineering

DECEMBER 5, 2020

Analytical Data Processing in SQL (Click here)

SQL 130

SQL Data Data Process Process 130

Striim

MAY 1, 2024

The sheer volume of data generated from the increasing package deliveries overwhelmed existing data management systems, underscoring a critical need for more advanced data handling capabilities. The absence of real-time data processing capabilities hindered UPS Capital’s risk management and rapid response efforts.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Knowledge Hut

APRIL 25, 2023

Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases. Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Snowflake

FEBRUARY 7, 2024

To calculate SPI, we identify a group of customer workloads that are stable and comparable in both amount of queries and data processed over the period presented. It embodies our commitment to provide transparency and accountability in continuously investing in the improvements that make Snowflake run your workloads faster.

SQL 79

SQL Database Designing Accessible 79

Christophe Blefari

OCTOBER 9, 2023

As a reminder Malloy is a new analytical language meant to generate SQL to query databases. In the last years Spark has been powering a lot of data use cases but with the modern data stack and more recently with DuckDB, Polars and smaller size OLAP technologies it allows a new way to do data processing.

Python 130

Python Data Database Java 130

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.

Hadoop 52

Hadoop Java Scala Programming Language 52

Data Engineering Podcast

JANUARY 7, 2024

Summary Data processing technologies have dramatically improved in their sophistication and raw throughput. Unfortunately, the volumes of data that are being generated continue to double, requiring further advancements in the platform capabilities to keep up.

Data Process 147

Data Process Process Data Lake High Quality Data 147

Knowledge Hut

NOVEMBER 2, 2023

Azure is being used by businesses for more sophisticated tasks including custom software development, artificial intelligence , and data science in addition to data processing and storage. Database Management Administer and manage Azure SQL Database, Azure Cosmos DB, and other database services on the platform.

Recruitment 52

Recruitment Cloud Computing Certification SQL 52