Rockset

AUGUST 30, 2021

You can also optionally use WHERE clauses to filter out data. Since only the aggregated data is now ingested and indexed into Rockset, this technique reduces the compute and storage required to track real-time metrics by a few orders of magnitude.

SQL 52

SQL Kafka MongoDB MySQL 52

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 107

Machine Learning Python Kafka Java 107

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 52

Consulting Raw Data Data Lake Data Pipeline 52

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 52

Consulting Raw Data Data Lake Data Pipeline 52

Rockset

DECEMBER 17, 2020

Essentially, Rockset is an indexing layer on top of DynamoDB and Amazon Kinesis, where we can join, search, and aggregate data from these sources. From there, we’ll create a data API for the SQL query we write in Rockset. When an associate converses with the customer, they can handle the customer’s situation appropriately.

Building 40

Building Aggregated Data SQL Data Ingestion 40

ProjectPro

DECEMBER 7, 2021

However, you can also pull data from centralized data sources like data warehouses to transform data further and build ETL pipelines for training and evaluating AI agents. Processing: It is a data pipeline component that decides the data flow implementation.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. DigDag: An open-source orchestrator for data engineering workflows.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

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 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

FEBRUARY 15, 2023

Yes, data warehouses can store unstructured data as a blob datatype. Data Transformation Raw data ingested into a data warehouse may not be suitable for analysis. Data engineers use SQL, or tools like dbt, to transform data within the data warehouse. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Rockset

OCTOBER 26, 2022

One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. And with the NFL season set to start in less than a month, we were in a bind. A Faster, Friendlier Solution We considered a few alternatives. Another was to scrap DynamoDB and find a traditional SQL database.

SQL 52

SQL NoSQL Database Aggregated Data 52

Rockset

MARCH 1, 2023

Collection Creation At collection creation time, I can also create ingest transformations including using SQL rollups to continuously aggregate data. In this example, I used ingest transformations to cast a date as a timestamp, parse a field and extract nested fields.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Ascend.io

MARCH 14, 2023

Usability In a data mesh, you publish your domain data to make it more feasible to digest and use. One approach is to publish more widely used aggregate data alongside record-level detail, as two separate data products. This is particularly useful if the aggregate rules are complex.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Usability In a data mesh, you publish your domain data to make it more feasible to digest and use. One approach is to publish more widely used aggregate data alongside record-level detail, as two separate data products. This is particularly useful if the aggregate rules are complex.

Government 52

Government Architecture Data Lake Data 52

Rockset

OCTOBER 4, 2022

Aggregator-Leaf-Tailer architecture used by Rockset In the following sections, we examine how some of these architectural differences impact the capabilities of Rockset and ClickHouse. Ingest Transformations and Rollups It is useful to be able to transform and rollup streaming data as it is being ingested.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Rockset

NOVEMBER 1, 2022

Here’s an example: SELECT NGRAMS(my_text_string, 1, 3) AS my_text_array, * FROM _input Aggregation It is common to pre-aggregate data before it arrives into Elasticsearch for use cases involving metrics. We often see ingest queries aggregate data by time.

Database-centric 52

Database-centric Pipeline-centric SQL Aggregated Data 52

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 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

SEPTEMBER 21, 2023

With native integrations for major cloud platforms like AWS, Azure, and Google Cloud, sending data to Elastic Cloud is straightforward. Its turn-key solutions further simplify data ingestion from multiple sources, including security systems and content repositories.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

FEBRUARY 8, 2023

Your data may be efficiently organized, cleaned, improved, and reliably moved across different data stores and data streams with the help of AWS Glue. You can write code to migrate, transform, and aggregate data from one source to another using the batch and streaming capabilities provided by AWS Glue ETL.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

JANUARY 25, 2022

Easy Processing- PySpark enables us to process data rapidly, around 100 times quicker in memory and ten times faster on storage. When it comes to data ingestion pipelines, PySpark has a lot of advantages. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems.

Big Data 52

Big Data Data Process Process Kafka 52

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 52

Big Data Project Metadata Programming Language 52

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. This may be okay for small datasets, but certainly isn’t feasible when you’re in the Big Data ecosystem.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

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 52

Analytics Application Data Warehouse Raw Data Kafka 52

AltexSoft

MARCH 14, 2023

Joining: combining data from multiple sources based on a common key or attribute. Modeling: transforming the data into a format that is suitable for analysis, including creating data structures, aggregating data, and adding derived fields.

IT 59

IT Data Warehouse Data Governance Data Lake 59