Aggregated Data, Architecture and Data Ingestion

A Breakthrough Architecture for Real-Time Analytics- An Overview of Compute-Compute Separation in Rockset

Rockset

MARCH 1, 2023

Rockset introduces a new architecture that enables separate virtual instances to isolate streaming ingestion from queries and one application from another. Benefits of Compute-Compute Separation In this new architecture, virtual instances contain the compute and memory needed for streaming ingest and queries.

Architecture

Architecture AWS SQL Cloud Storage

Striim Deemed ‘Leader’ and ‘Fast Mover’ by GigaOm Radar Report for Streaming Data Platforms

Striim

JULY 31, 2024

Why Striim Stands Out As detailed in the GigaOm Radar Report, Striim’s unified data integration and streaming service platform excels due to its distributed, in-memory architecture that extensively utilizes SQL for essential operations such as transforming, filtering, enriching, and aggregating data.

Aggregated Data

Aggregated Data Data Ingestion Java Kafka

Druid Deprecation and ClickHouse Adoption at Lyft

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka

Kafka Data Ingestion Datasets Architecture

Webinars

Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline

Data Pipeline Architecture Kafka AWS

What is a Data Pipeline (and 7 Must-Have Features of Modern Data Pipelines)

Striim

OCTOBER 11, 2024

These steps guarantee that data is accurate, reliable, and meaningful by the time it reaches its destination, making it possible for teams to generate insights and make data-driven decisions. This architecture can vary based on the needs of the organization and the type of data being processed.

Data Pipeline

Data Pipeline MongoDB Unstructured Data Data Lake

Complete Guide to Data Transformation: Basics to Advanced

Ascend.io

OCTOBER 28, 2024

Intermediate Data Transformation Techniques Data engineers often find themselves in the thick of transforming data into formats that are not only usable but also insightful. Intermediate data transformation techniques are where the magic truly begins.

Raw Data

Raw Data Datasets Aggregated Data Data Pipeline

Comparing ClickHouse vs Rockset for Event and CDC Streams

Rockset

OCTOBER 4, 2022

Change data capture (CDC) streams from OLTP databases, which may provide sales, demographic or inventory data, are another valuable source of data for real-time analytics use cases. Architecture ClickHouse was developed, beginning in 2008, to handle web analytics use cases at Yandex in Russia. Flink, Kafka and MySQL.

MySQL

MySQL Kafka Aggregated Data Architecture

Azure Data Engineer Roles and Responsibilities in 2024

Knowledge Hut

MARCH 20, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineer

Data Engineer Data Engineering Engineering Data Governance

Azure Data Engineer Roles and Responsibilities 2024

Knowledge Hut

MARCH 15, 2024

The job description for Azure data engineer that I have elucidated below focuses more on foundational tasks while providing opportunities for learning and growth within the field: Data ingestion: This role involves assisting in the process of collecting and importing data from various sources into Azure storage solutions.

Data Engineer

Data Engineer Data Engineering Engineering Data Governance

Tips to Build a Robust Data Lake Infrastructure

DareData

JULY 5, 2023

Understanding the Architecture No company is alike and no infrastructure will be alike. Although there are some guidelines that you can follow when setting up a data infrastructure, each company has it's own needs, processes and organizational structure. Data Sources: How different are your data sources?

Data Lake

Data Lake Building Raw Data ETL Tools

What Is a Data Mesh?

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. It provides a more distributed, decentralized, and resilient approach to data management. So, what’s the solution?

Government

Government Architecture Data Lake Data

What Is a Data Mesh?

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. It provides a more distributed, decentralized, and resilient approach to data management. So, what’s the solution?

Government

Government Architecture Data Lake Data

Consulting Case Study: Job Market Analysis

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting

Consulting Raw Data Data Lake Data Pipeline

Consulting Case Study: Job Market Analysis

WeCloudData

OCTOBER 19, 2021

Furthermore, one cannot combine and aggregate data from publicly available job boards into custom graphs or dashboards. The client needed to build its own internal data pipeline with enough flexibility to meet the business requirements for a job market analysis platform & dashboard.

Consulting

Consulting Raw Data Data Lake Data Pipeline

Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. So how can the Kafka ecosystem help here?

Machine Learning

Machine Learning Python Kafka Java

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

AUGUST 24, 2021

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

Data Engineer

Data Engineer Data Engineering Coding Project

5 Steps for Migrating from Elasticsearch to Rockset for Real-Time Analytics

Rockset

NOVEMBER 1, 2022

The lack of proper joins, immutable indexes that need constant vigil, a tightly coupled compute and storage architecture, and highly specific domain knowledge needed to develop and operate it has left many engineers seeking alternatives. We often see ingest queries aggregate data by time.

Database-centric

Database-centric SQL Pipeline-centric Aggregated Data

The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

SEPTEMBER 21, 2023

These diverse use cases demonstrate the engine’s versatility, making it a popular choice for organizations dealing with various data types and requiring fast, actionable insights. Key components of the Elasticsearch architecture. Each document is a collection of fields, the basic data units to be searched.

Engineering

Engineering NoSQL Programming Language Java

Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools

ETL Tools Hadoop Relational Database Unstructured Data

A Beginner’s Guide to Learning PySpark for Big Data Processing

ProjectPro

JANUARY 25, 2022

Features of PySpark The PySpark Architecture Popular PySpark Libraries PySpark Projects to Practice in 2022 Wrapping Up FAQs Is PySpark easy to learn? Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things.

Big Data

Big Data Data Process Process Kafka

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. The ETL code for your data is automatically generated by AWS Glue when you specify your ETL process in the drag-and-drop job editor. How Does AWS Glue Work?

AWS

AWS Scala Metadata Data Lake

20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data

Big Data Project Metadata Programming Language

What is Data Engineering? Everything You Need to Know in 2022

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. Data always has to be extracted in some manner first from a source of data, but what should happen next is not as simple.

Data Engineer

Data Engineer Data Engineering Engineering Data Governance

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

IT

IT Data Warehouse Data Governance Data Lake

Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

APRIL 15, 2022

Rockset not only continuously ingests data, but also can “rollup” the data as it is being generated. By using SQL to aggregate data as it is being ingested, this greatly reduces the amount of data stored (5-150x) as well as the amount of compute needed queries (boosting performance 30-100x).

Analytics Application

Analytics Application Data Warehouse Kafka Raw Data

Data Engineering Digest

A Breakthrough Architecture for Real-Time Analytics- An Overview of Compute-Compute Separation in Rockset

Striim Deemed ‘Leader’ and ‘Fast Mover’ by GigaOm Radar Report for Streaming Data Platforms

Webinars

Trending Sources

Druid Deprecation and ClickHouse Adoption at Lyft

Webinars

Data Pipeline- Definition, Architecture, Examples, and Use Cases

What is a Data Pipeline (and 7 Must-Have Features of Modern Data Pipelines)

Complete Guide to Data Transformation: Basics to Advanced

Comparing ClickHouse vs Rockset for Event and CDC Streams

Azure Data Engineer Roles and Responsibilities in 2024

Azure Data Engineer Roles and Responsibilities 2024

Tips to Build a Robust Data Lake Infrastructure

What Is a Data Mesh?

What Is a Data Mesh?

Consulting Case Study: Job Market Analysis

Consulting Case Study: Job Market Analysis

Machine Learning with Python, Jupyter, KSQL and TensorFlow

20+ Data Engineering Projects for Beginners with Source Code

5 Steps for Migrating from Elasticsearch to Rockset for Real-Time Analytics

The Good and the Bad of the Elasticsearch Search and Analytics Engine

Sqoop vs. Flume Battle of the Hadoop ETL tools

A Beginner’s Guide to Learning PySpark for Big Data Processing

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

20 Best Open Source Big Data Projects to Contribute on GitHub

What is Data Engineering? Everything You Need to Know in 2022

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Handling Out-of-Order Data in Real-Time Analytics Applications

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