Knowledge Hut

JUNE 26, 2023

Get ready to delve into fascinating data engineering project concepts and explore a world of exciting data engineering projects in this article. Best Data Science certifications online or offline are available to assist you in establishing a solid foundation for every end-to-end data engineering project.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. How much python should you know to become a data engineer? In 2017, Gartner predicted that 85%of the data-based projects would fail and deliver the desired results.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

dbt Developer Hub

NOVEMBER 28, 2021

Airflow and dbt are often framed as either / or: You either build SQL transformations using Airflow’s SQL database operators (like SnowflakeOperator ), or develop them in a dbt project. You either orchestrate dbt models in Airflow, or you deploy them using dbt Cloud. Let’s export log events into BigQuery. “I

Google Cloud 52

Google Cloud SQL Cloud Consulting 52

Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based.

Kafka 80

Kafka Python Process Google Cloud 80

Christophe Blefari

MARCH 31, 2023

Except the fact that they have a pretty bad vocabulary for things, it works, and the UI is surprisingly pleasant to use. My personal preference hierarchy changed with this experience, which is subjective, is GCP > Azure > AWS. Pricing changes First, a new BigQuery pricing model. But obviously it changed.

Bytes 130

Bytes Data Google Cloud Education 130

Data Engineering Podcast

JUNE 19, 2022

In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP.

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Metadata MongoDB Scala MySQL 130

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. Most recruiters look for real-world project experience and shortlist the resumes based on hands-on experience working on data engineering projects.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

FEBRUARY 20, 2024

There’s the dichotomy between batch and streaming, between all-in-one platforms and niche connectors in your modern data stack, and the trade-off between ease-of-use and powerful customization options. One thing’s for certain: you definitely don’t want to be writing pipelines in Python anymore.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Knowledge Hut

FEBRUARY 7, 2023

In this blog, we go through what a Data Science Platform is, the different types of platforms, and how they can be used to bring value to the business so that the big corporates can stay in the race to conquer the market of the future. Typically, data science projects involve using an abundance of ls (eg. They are: 1.

Data Science 52

Data Science Google Cloud Programming Language AWS 52

Towards Data Science

JULY 24, 2023

Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technologies like Snowflake (2012), Databricks (2013), and BigQuery (2010). Let’s dive into the current landscape and recent evolutions before looking closer at why that may be the case.

Metadata 97

Metadata Data Warehouse Data Lake Data Science 97

ProjectPro

JULY 30, 2021

Software and applications are used on a subscription basis. What are some popular use cases for cloud computing? With the advent of cloud storage, customers could only pay for the storage they used. Test and Development - Cloud provides ready-to-use, customised, and fully set up resources. E.g. AWS Cloud Connect.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

JANUARY 31, 2022

With around 5774 companies using it, Snowflake has recently been added to the top 20 most valued worldwide unicorns and the top 10 most expensive US unicorns. Snowflake provides data warehousing, processing, and analytical solutions that are significantly quicker, simpler to use, and more adaptable than traditional systems.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. Amazon and Google are the big bulls in cloud technology, and the battle between AWS and GCP has been raging on for a while.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

Ascend.io

MAY 16, 2023

So, globally speaking, we operate multi-cloud architectures in the extreme, with some people on AWS, some on GCP, and some on Azure. That was Phase One, just to equip us to be able to do basic trend analysis and tell the story on demand, rather than doing it ad hoc. Probably one flavor of almost everything you can imagine!

Big Data 52

Big Data Data Architecture Datasets 52

Confluent

SEPTEMBER 20, 2019

BigQuery, Amazon Redshift, and MongoDB Atlas) and caches (e.g., A distributed streaming platform combines reliable and scalable messaging, storage, and processing capabilities into a single, unified platform that unlocks use cases other technologies individually can’t. CPU, memory, and disk) to use.

Kafka 21

Kafka Management Cloud AWS 21

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Table of Contents What is a Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

Monte Carlo

JULY 18, 2023

Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technologies like Snowflake (2012), Databricks (2013), and BigQuery (2010). Let’s dive into the current landscape and recent evolutions before looking closer at why that may be the case.

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Monte Carlo

JULY 18, 2023

Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technologies like Snowflake (2012), Databricks (2013), and BigQuery (2010). Let’s dive into the current landscape and recent evolutions before looking closer at why that may be the case.

Metadata 40

Metadata Data Warehouse Data Lake Government 40

Towards Data Science

NOVEMBER 4, 2023

We will discuss how to use this knowledge to power advanced analytics pipelines and operational excellence. Image by author It also might be a datalake in the center and it depends on the type of our data platform and tools we use. If you know a bit of Python it would be a trivial task. What is it? Data warehouse exmaple.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. From data sources and use cases to industry and company size, how a company structures its data platform will depend on a variety of critical factors.

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Building BI Data Lake Data Governance 52