Aggregated Data, Data Ingestion, Events and Process

Aggregated Data

Data Ingestion

Events

Process

How Snowflake Enhanced GTM Efficiency with Data Sharing and Outreach Customer Engagement Data

Snowflake

APRIL 9, 2024

However, that data must be ingested into our Snowflake instance before it can be used to measure engagement or help SDR managers coach their reps — and the existing ingestion process had some pain points when it came to data transformation and API calls. Each of these sources may store data differently.

BI Data Ingestion Data Aggregated Data

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

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How to Optimize the Developer Experience for Monumental Impact

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

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Trending Sources

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.

Machine Learning

Machine Learning Python Kafka Java

Webinars

How to Optimize the Developer Experience for Monumental Impact

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

MORE WEBINARS

Tips to Build a Robust Data Lake Infrastructure

DareData

JULY 5, 2023

In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently. To overcome this challenge, many companies are turning to Data Lake solutions, which provide a centralized and scalable platform for storing, processing, and analyzing data.

Data Lake

Data Lake Building Raw Data ETL Tools

How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

AUGUST 30, 2021

However, for many use cases at huge volumes — such as a Kafka topic that streams tens of TBs of data every day — it becomes prohibitively expensive to index the raw data stream and then calculate the desired metrics downstream at query processing time. You can also optionally use WHERE clauses to filter out data.

SQL

SQL Kafka MongoDB MySQL

Build Internal Apps in Minutes with Retool and Rockset: A Customer 360 Example

Rockset

DECEMBER 17, 2020

Overview of the Customer 360 App Our app will make use of real-time data on customer orders and events. We’ll use Rockset to get data from different sources and run analytical queries that power our app in Retool. From there, we’ll create a data API for the SQL query we write in Rockset.

Building

Building Aggregated Data SQL Data Ingestion

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

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline

Data Pipeline Architecture Kafka AWS

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

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDD uses a key to partition data into smaller chunks.

Big Data

Big Data Data Process Process Kafka

Comparing ClickHouse vs Rockset for Event and CDC Streams

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. ClickHouse has several storage engines that can pre-aggregate data.

MySQL

MySQL Kafka Aggregated Data Architecture

20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering

Data Engineering Data Engineer Coding Project

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

FEBRUARY 8, 2023

In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. AWS Glue automates several processes as well.

AWS

AWS Scala Metadata Data Lake

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

Rockset

MARCH 1, 2023

As a result, compute contention ensues, causing several problems for customers and prospects: User-facing analytics in my SaaS application can only update every 30 minutes since the underlying database becomes unstable whenever I try to process streaming data continuously.

Architecture

Architecture AWS SQL Cloud Storage

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.

ETL Tools

ETL Tools Hadoop Relational Database Unstructured Data

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

AltexSoft

SEPTEMBER 21, 2023

It interacts through comprehensive REST APIs , processing and returning results in JSON format. ESRE enables advanced relevance ranking, natural language processing (NLP), and the ability to work with large language models (LLMs) like OpenAI’s GPT-3 and GPT-4. Analysis of logs, metrics, and security events.

Engineering

Engineering NoSQL Programming Language Java

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

Rockset

NOVEMBER 1, 2022

Step 1: Data Acquisition Elasticsearch is rarely the system of record which means the data in it comes from somewhere else for real-time analytics. Rockset has built-in connectors to stream real-time data for testing and simulating production workloads including Apache Kafka , Kinesis and Event Hubs.

Database-centric

Database-centric Pipeline-centric SQL Aggregated Data

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

phData: Data Engineering

JANUARY 3, 2022

The best option will vary depending on whether your data is structured or unstructured (or even semi-structured), normalized or denormalized, and whether you need data in a row or columnar data format. Is your data key/value-based? Are there complex relationships between the data? Data must also be performant.

Data Engineering

Data Engineering Data Engineer Engineering Data Governance

20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

NOVEMBER 15, 2021

It derives its name “Beam” which is from “Batch” + “Stream” from its functionalities for both batch and streaming the parallel processing pipelines for data. You can contribute to Apache Beam open-source big data project here: [link] 2. It comes with programming interfaces for entire clusters.

Big Data

Big Data Project Metadata Programming Language

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

Rockset

APRIL 15, 2022

It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. Transmitting out-of-order data is not the issue.

Analytics Application

Analytics Application Data Warehouse Raw Data Kafka

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

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT Data Warehouse Data Governance Data Lake

Data Engineering Digest

How Snowflake Enhanced GTM Efficiency with Data Sharing and Outreach Customer Engagement Data

Druid Deprecation and ClickHouse Adoption at Lyft

Webinars

Trending Sources

Machine Learning with Python, Jupyter, KSQL and TensorFlow

Webinars

Tips to Build a Robust Data Lake Infrastructure

How Rockset Enables SQL-Based Rollups for Streaming Data

Build Internal Apps in Minutes with Retool and Rockset: A Customer 360 Example

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

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

Comparing ClickHouse vs Rockset for Event and CDC Streams

20+ Data Engineering Projects for Beginners with Source Code

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

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

Sqoop vs. Flume Battle of the Hadoop ETL tools

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

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

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

20 Best Open Source Big Data Projects to Contribute on GitHub

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

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

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