Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools! What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Rockset

MAY 17, 2022

Limitations of NoSQL SQL supports complex queries because it is a very expressive, mature language. Complex SQL queries have long been commonplace in business intelligence (BI). And when systems such as Hadoop and Hive arrived, it married complex queries with big data for the first time.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Cloud Academy

JANUARY 27, 2022

Data engineering is the process of designing and implementing solutions to collect, store, and analyze large amounts of data. The data then gets prepared in formats to be used by people such as business analysts, data analysts, and data scientists. What does a data engineer do?

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Knowledge Hut

MAY 4, 2023

Data engineering is a prominent yet emerging technological field that is currently enjoying high demand. Salaries for data engineers vary across the globe, depending on various factors such as location, experience, skills and Data Engineer training and certifications taken by the professionals.

Data Engineering 52

Data Engineering Data Engineer Engineering Banking 52

Knowledge Hut

JUNE 20, 2023

Let's find out the differences between a data scientist and a machine learning engineer below to make an informative decision. Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 26, 2023

Data Science is a combination of several disciplines including Mathematics and Statistics, Data Analysis, Machine Learning, and Computer Science. Data Science is a huge umbrella with a plethora of roles available in the field such as a Data Scientist, Data Engineer, BI Developer, Data and Analytics Manager, etc.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Data Engineering Podcast

FEBRUARY 11, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? What impact has the 10.0

PostgreSQL 100

PostgreSQL NoSQL Google Cloud MongoDB 100

Databand.ai

DECEMBER 13, 2022

The Top 25 Data Engineering Influencers and Content Creators on LinkedIn Ryan Yackel 2022-12-13 10:23:19 Interested in data engineering? LinkedIn is full of influencers sharing new ideas and sparking conversations on all kinds of topics, and data engineering is no exception. You’ve come to the right place.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

JANUARY 18, 2024

Data Scientist-(average salary: Rs 11 lakhs, can reach up to Rs 25 lakhs) Data analyst-(average salary: Rs 4.2 lakhs) Data architect-(average salary: Rs 23 lakhs, can reach up to Rs 38.5 lakhs) Data engineer-(average salary: Rs8.1 lakhs, can reach up to Rs 11.5 lakhs, can reach up to Rs 21.

Data Science 52

Data Science Computer Science Programming Language NoSQL 52

Monte Carlo

NOVEMBER 20, 2023

Far from a mere “copy-paste” job, data migrations can be deceptively tricky and one of the most challenging aspects of a data engineer’s job. But as businesses pivot and technologies advance, data migrations are—regrettably—unavoidable.

MongoDB 52

MongoDB ETL Tools Database Data 52

ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Data Engineering Podcast

APRIL 14, 2024

In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database. Data lakes are notoriously complex. Can you describe what constitutes a NoSQL database? SQL database? changed the landscape for NoSQL engines?

Non-relational Database 147

Non-relational Database Relational Database Database Designing 147

Rockset

MAY 12, 2022

However, these databases tend to sacrifice support for complex SQL queries at any scale. Instead, these database makers have offloaded complex analytics onto application code and their developers, who have neither the skills nor the time to constantly update queries as data sets evolve. It provides instant views of the real-time data.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Electronics 52

Rockset

AUGUST 11, 2022

I had the pleasure of recently hosting a data engineering expert discussion on a topic that I know many of you are wrestling with – when to deploy batch or streaming data in your organization’s data stack. Andreas also produces the well-known ‘Plumbers of Data Science’ blog and podcast , as well as a YouTube channel.

Bytes 52

Bytes Consulting Kafka MongoDB 52

Rockset

APRIL 3, 2020

Decision taken to write data into suitable DynamoDB tables Handle scenario when data is out of range and send email to the configured email address via SNS DynamoDB This project uses DynamoDB to store the large volume of data that would be generated in a live environment. Data is stored in the DB in JSON format.

Data Pipeline 40

Data Pipeline Systems Management NoSQL 40

Knowledge Hut

DECEMBER 21, 2023

Data Science is the world's most rapidly growing sector and data engineers are at the forefront. In this article, we will understand the promising data engineer career outlook and what it takes to succeed in this role. What is Data Engineering? What are the Data Engineer Career Opportunities?

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Zalando Engineering

JUNE 6, 2016

Big Data Engineer The term Big Data was first coined in the 1990s by John Mashey , referring to a large set of data that is almost impossible to manage using traditional business intelligence tools. A database querying language like SQL is also part of their arsenal.

Big Data 40

Big Data Programming Language MongoDB NoSQL 40

DareData

JANUARY 30, 2023

Learn the most important data engineering concepts that data scientists should be aware of. As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. DigDag: An open-source orchestrator for data engineering workflows.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

The exam tests the use of Cloudera products such as Cloudera Data Visualization, Cloudera Machine Learning, Cloudera Data Science Workbench, Cloudera Data Warehouses well as SQL, Apache Nifi, Apache Hive and other open source technologies. No prior experience is required. It is a 13-course series.

Big Data 52

Big Data Certification Hadoop Scala 52

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it. Skills acquired : Core data concepts. Now, it's different.

Database 52

Database Certification MongoDB MySQL 52

Rockset

JUNE 7, 2021

Some databases like SQL Server have this functionality built in; others require database triggers to increment the number any time a modification is made to the record. These CDC implementations are offered in the form of configurable connectors for systems such as MongoDB , DynamoDB , MySQL , Postgres and others.

IT 40

IT Kafka Database MongoDB 40

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Knowledge Hut

MAY 23, 2024

All the different processes that data science uses for analyzing & extracting insight from data require appropriate tools. A data science professional, data analyst, data engineer, and data scientist need to have high proficiency in these tools to excel in the data science career.

Data Science 52

Data Science MongoDB Programming Language Unstructured Data 52

Knowledge Hut

SEPTEMBER 6, 2023

Once the data is tailored to your requirements, it then should be stored in a warehouse system, where it can be easily used by applying queries. Some of the most popular database management tools in the industry are NoSql, MongoDB and oracle. You will learn about Python, SQL, statistical modeling and data analysis.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

ProjectPro

NOVEMBER 14, 2015

Hadoop ecosystem has a very desirable ability to blend with popular programming and scripting platforms such as SQL, Java , Python, and the like which makes migration projects easier to execute. From Data Engineering Fundamentals to full hands-on example projects , check out data engineering projects by ProjectPro 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Rockset

SEPTEMBER 3, 2020

MongoDB’s Advantages & Disadvantages MongoDB has comprehensive aggregation capabilities. You can run many analytic queries on MongoDB without exporting your data to a third-party tool. In this situation, the MongoDB cluster doesn’t have to keep up with the read requests. This is never a good thing.

MongoDB 40

MongoDB PostgreSQL SQL Database 40

ProjectPro

MAY 19, 2015

Thus, professionals must learn Hadoop to ramp up on the big data technology as Hadoop is soon going to be identified as a must have skill by all big data companies. According to Technology Research Organization, Wikibon-“Hadoop and NoSQL software and services are the fastest growth technologies in the data market.”

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

Christophe Blefari

AUGUST 4, 2023

Race data will be partitioned per day, but as the Tour is already done, it will be a bit different than in real life environment. Because I'm convinced that to learn data engineering you need to experiment real life pipelines running every day to experiment the morning firefighting. Read Data Engineering Weekly.

Google Cloud 225

Google Cloud MongoDB NoSQL Data 225

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

AltexSoft

JUNE 26, 2023

Both data integration and ingestion require building data pipelines — series of automated operations to move data from one system to another. For this task, you need a dedicated specialist — a data engineer or ETL developer. Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

JULY 29, 2022

What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? Under the hood, the framework divides a chunk of Big Data into smaller, digestible parts and allocates them across multiple commodity machines to be processed in parallel. How data engineering works under the hood.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

NOVEMBER 7, 2023

Top Roles Data Engineer A data engineer is in charge of a company's data and put it to strategic use. Company data is frequently utilized to generate company insights to help decision-making, or the data may be included in the company's own products or services.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

AltexSoft

MAY 14, 2021

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Data Science Blog: Data Engineering

SEPTEMBER 24, 2021

This ensures that all data in the database is valid even if we execute big transactions which include multiple statements (e. SQL) composed into one transaction updating many data rows in the database. Redis, CouchDB, MongoDB, Cosmos DB, Cassandra, ElasticSearch, Neo4J, OrientDB or ArangoDB are just some popular examples.

NoSQL 52

NoSQL Data Warehouse Database MongoDB 52

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JANUARY 31, 2023

This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files. Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

OCTOBER 8, 2021

It’s well-suited for everyone from data engineers to business users with little or no tech expertise. Data profiling and cleansing. Xplenty allows organizations that don’t have a data engineering team to perform data profiling and cleansing procedures automatically. They include NoSQL databases (e.g.,

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52