Confluent

FEBRUARY 6, 2019

This can either be built natively around the Kafka ecosystem, or you could use Kafka just for ingestion into another storage and processing cluster such as HDFS or AWS S3 with Spark. New MQTT input data can directly be used in real time to make predictions. For now, we’ll focus on Kafka. So what’s the big deal?

Machine Learning 106

Machine Learning Python Kafka Java 106

ProjectPro

APRIL 20, 2017

The collection of these projects on Hadoop and Spark will help professionals master the big data and Hadoop ecosystem concepts learnt during their hadoop training. ” – This is one of the most common question asked by students who complete Hadoop Training and Certification from ProjectPro. Extracting data from APIs using Python.

Hadoop 40

Hadoop Big Data Coding Project 40

Rockset

SEPTEMBER 13, 2022

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available. DynamoDB is a NoSQL database provided by AWS.

SQL 52

SQL Database Relational Database AWS 52

Monte Carlo

FEBRUARY 15, 2023

On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. In both of these cases, the data needs to be consolidated. Data Transformation Raw data ingested into a data warehouse may not be suitable for analysis.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS).

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

ProjectPro

JANUARY 25, 2022

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. PySpark SQL and Dataframes A dataframe is a shared collection of organized or semi-structured data in PySpark.

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

SEPTEMBER 6, 2023

Monitor and optimize operational resources in Azure SQL Optimize query performance in Azure SQL Automate database tasks for Azure SQL Plan and implement a high availability and disaster recovery environment. Passing the exam means one has gained a significant knowledge of SQL and its use while working on Oracle Database servers.

Database 52

Database Certification MongoDB MySQL 52

Rockset

MARCH 1, 2023

Step 1: Create a Collection that Syncs Twitter Data from the Kinesis Stream In preparation for the walk-through of compute-compute separation, I set up an integration to Amazon Kinesis using AWS Cross-Account IAM roles and AWS Access Keys. The option for continuous refresh is currently available in early access.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Rockset

OCTOBER 26, 2022

Also, DynamoDB, as a NoSQL database, doesn’t support SQL commands such as JOINING multiple tables. One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. Another was to scrap DynamoDB and find a traditional SQL database. Both would have required a lot of work.

SQL 52

SQL NoSQL Database Aggregated Data 52

Rockset

FEBRUARY 16, 2024

They also wanted the capability to add new metrics, data points and run ad-hoc analysis as they continued to build out real-time monitoring. Cloud offering: Klarna is built on AWS and made the decision early on to use cloud services and not get into the game of infrastructure management.

Architecture 59

Architecture SQL Data Warehouse Database 59

ProjectPro

AUGUST 24, 2021

Salary of Data Engineers Data Engineering Tools Skills Required to Become a Data Engineer Responsibilities of a Data Engineer FAQS on Data Engineering Projects Data Engineering Projects List There are a few data-related skills that most data engineering practitioners must possess.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

JANUARY 26, 2022

Here’s the video explaining how data engineers work. Data analysts are responsible for building reports and dashboards on top of pre-processed data and drawing out insights from it. They work with Excel, SQL code, and analytics tools to perform ad-hoc analyses and forecasting. Strong SQL skills.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

Rockset

AUGUST 26, 2022

They also looked at using AWS-hosted Spark as its database engine and serving up queries to a Tableau dashboard. Data is uploaded to Rockset from S3 every 3-5 minutes. Rockset also powerfully supports SQL, with which all of Meza’s developers were experts. They demoed but quickly eliminated Snowflake.

IT 52

IT Food Data Lake Aggregated Data 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

SEPTEMBER 21, 2023

Just as you have databases and tables in SQL, you have indices and documents in Elasticsearch. You would query against these indices when you are searching for specific data. You can stream logs, metrics, and other data from your apps, endpoints, and infrastructure, whether cloud-based, on-premises, or a mix of both.

Engineering 52

Engineering NoSQL Programming Language Java 52