Data Engineering Podcast

JANUARY 21, 2024

For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

MARCH 1, 2018

News on Hadoop - February 2018 Kyvos Insights to Host Webinar on Accelerating Business Intelligence with Native Hadoop BI Platforms. The leading big data analytics company Kyvo Insights is hosting a webinar titled “Accelerate Business Intelligence with Native Hadoop BI platforms.” PRNewswire.com, February 1, 2018.

Hadoop 52

Hadoop NoSQL Retail BI 52

Knowledge Hut

DECEMBER 26, 2023

Most Popular Programming Certifications C & C++ Certifications Oracle Certified Associate Java Programmer OCAJP Certified Associate in Python Programming (PCAP) MongoDB Certified Developer Associate Exam R Programming Certification Oracle MySQL Database Administration Training and Certification (CMDBA) CCA Spark and Hadoop Developer 1.

Certification 98

Certification Programming MongoDB R (Programming) 98

ProjectPro

DECEMBER 17, 2021

All this data is stored in a database that requires SQL-based queries for retrieval and transformations, making it essential for every data professional to learn SQL for data science and machine learning. Table of Contents Why SQL for Data Science? What is SQL? Why SQL for Data Science?

Data Science 52

Data Science SQL NoSQL Programming Language 52

ProjectPro

MAY 2, 2016

News on Hadoop-April 2016 Cutting says Hadoop is not at its peak but at its starting stages. Datanami.com At his keynote address in San Jose, Strata+Hadoop World 2016, Doug Cutting said that Hadoop is not at its peak and not going to phase out. Source: [link] ) Dr. Elephant will now solve your Hadoop flow problems.

Hadoop 52

Hadoop NoSQL Hospitality Big Data 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed with SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. Hard Skills SQL, which includes memorizing a query and resolving optimized queries. Apache Hadoop-based analytics to compute distributed processing and storage against datasets.

Data Engineer 52

Data Engineer Data Engineering Engineering Non-relational Database 52

ProjectPro

MAY 2, 2017

News on Hadoop-April 2017 AI Will Eclipse Hadoop, Says Forrester, So Cloudera Files For IPO As A Machine Learning Platform. Apache Hadoop was one of the revolutionary technology in the big data space but now it is buried deep by Deep Learning. Hortonworks unveiled this use case of SQL through Apache Hive 2.0

Hadoop 52

Hadoop Entertainment Data Lake Big Data 52

ProjectPro

JULY 21, 2015

Apache Hive is an effective standard for SQL-in- Hadoop. Hive is a front end for parsing SQL statements, generating logical plans, optimizing logical plans, translating them into physical plans which are executed by MapReduce jobs. Impala is an open source SQL query engine developed after Google Dremel.

Hadoop 40

Hadoop SQL NoSQL Kafka 40

ProjectPro

OCTOBER 3, 2016

News on Hadoop-September 2016 HPE adapts Vertica analytical database to world with Hadoop, Spark.TechTarget.com,September 1, 2016. has expanded its analytical database support for Apache Hadoop and Spark integration and also to enhance Apache Kafka management pipeline. To compete in a field of diverse data tools, Vertica 8.0

Hadoop 52

Hadoop Database-centric Pipeline-centric Big Data 52

Edureka

AUGUST 29, 2024

Databases: Knowledgeable about SQL and NoSQL databases. Big Data Technologies: Aware of Hadoop, Spark, and other platforms for big data. Learn Key Technologies Programming Languages: Language skills, either in Python, Java, or Scala. Data Warehousing: Experience in using tools like Amazon Redshift, Google BigQuery, or Snowflake.

Data Engineer 40

Data Engineer Data Engineering Engineering Generalist 40

Knowledge Hut

MARCH 20, 2024

Handling databases, both SQL and NoSQL. Databases and tools: AI engineers must be adept at working with different forms of data and know how to handle SQL and NoSQL databases. Knowledge of data tools and platforms like Apache Spark, AWS S3, and Hadoop is also essential.

Engineering 52

Engineering NoSQL Programming Language Deep Learning 52

ProjectPro

APRIL 1, 2016

News on Hadoop- March 2016 Hortonworks makes its core more stable for Hadoop users. PCWorld.com Hortonworks is going a step further in making Hadoop more reliable when it comes to enterprise adoption. Source: [link] ) Syncsort makes Hadoop and Spark available in native Mainframe. March 1, 2016. March 4, 2016.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

ProjectPro

NOVEMBER 10, 2016

Let’s help you out with some detailed analysis on the career path taken by hadoop developers so you can easily decide on the career path you should follow to become a Hadoop developer. What do recruiters look for when hiring Hadoop developers? Do certifications from popular Hadoop distribution providers provide an edge?

Hadoop 52

Hadoop NoSQL Java Electronics 52

AltexSoft

MAY 14, 2021

Apache Hadoop. Apache Hadoop is a set of open-source software for storing, processing, and managing Big Data developed by the Apache Software Foundation in 2006. Hadoop architecture layers. As you can see, the Hadoop ecosystem consists of many components. NoSQL databases. Source: phoenixNAP.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. How is Hadoop related to Big Data? How is Hadoop related to Big Data? Define and describe FSCK.

Big Data 52

Big Data Hadoop Relational Database AWS 52

U-Next

MARCH 1, 2023

A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial.

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

U-Next

AUGUST 17, 2022

SQL – A database may be used to build data warehousing, combine it with other technologies, and analyze the data for commercial reasons with the help of strong SQL abilities. The job description for Data Engineers may require them to eventually specialize in one or more SQL kinds (such as advanced modeling, big data, etc.).

Data Engineer 52

Data Engineer Data Engineering Pipeline-centric Database-centric 52

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

Data Engineering Podcast

FEBRUARY 11, 2018

Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? Is timescale compatible with systems such as Amazon RDS or Google Cloud SQL? How is Timescale implemented and how has the internal architecture evolved since you first started working on it? What impact has the 10.0 What impact has the 10.0

PostgreSQL 100

PostgreSQL NoSQL Google Cloud MongoDB 100

Knowledge Hut

APRIL 25, 2023

Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Rockset

NOVEMBER 1, 2018

Over a decade after the inception of the Hadoop project, the amount of unstructured data available to modern applications continues to increase. Moreover, despite forecasts to the contrary, SQL remains the lingua franca of data processing; today's NoSQL and Big Data infrastructure platform usage often involves some form of SQL-based querying.

Raw Data 40

Raw Data SQL Unstructured Data NoSQL 40

ProjectPro

MAY 13, 2015

Table of Contents MongoDB NoSQL Database Certification- Hottest IT Certifications of 2015 MongoDB-NoSQL Database of the Developers and for the Developers MongoDB Certification Roles and Levels Why MongoDB Certification? The three next most common NoSQL variants are Couchbase, CouchDB and Redis.

NoSQL 40

NoSQL MongoDB Certification Database 40

Knowledge Hut

NOVEMBER 28, 2023

SQL Today, more and more cloud-based systems add SQL-like interfaces that allow you to use SQL. Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023. ETL is central to getting your data where you need it.

Data Engineer 52

Data Engineer Data Engineering Engineering Generalist 52

ProjectPro

SEPTEMBER 9, 2021

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

JANUARY 18, 2024

SQL SQL is essential if you want to work with relational databases at any level of detail. SQL databases are structured differently than NoSQL databases - they store data in tables rather than documents or graphs - but they're still very useful when you want to structure your data in a way that makes sense for humans (and computers).

Data Science 52

Data Science Computer Science Programming Language NoSQL 52

Knowledge Hut

APRIL 26, 2024

Now that the issue of storage of big data has been solved successfully by Hadoop and various other frameworks, the concern has shifted to processing these data. Another main aspect of this position is database design (RDBMS, NoSQL, and NewSQL), data warehousing, and setting up a data lake.

Data Science 52

Data Science Machine Learning Hadoop Algorithm 52

ProjectPro

NOVEMBER 14, 2015

Apache Hadoop and Apache Spark fulfill this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Table of Contents Why Apache Hadoop?

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

APRIL 23, 2024

It employs technologies such as Apache Hadoop, Apache Spark, and NoSQL databases to handle the immense scale and complexity of big data. Technologies like Hadoop, Spark, Hive, Cassandra, etc. Unlike big data warehouse, big data focuses on processing and analyzing data in its raw and unstructured form.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Edureka

JULY 4, 2024

It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Additionally, EMR can integrate with Amazon RDS and Amazon DynamoDB for any relational or NoSQL database requirements that the applications have.

AWS 52

AWS Amazon Web Services Hadoop Big Data 52

Monte Carlo

JUNE 2, 2024

Based on our job postings analysis, here are some key areas of expertise to focus on: Technical Expertise Programming Languages: Proficiency in SQL (mentioned in 88% of job postings) and Python (78%) is essential. There you can build your skills in SQL, Python, data modeling, and basic networking.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Monte Carlo

JUNE 2, 2024

Based on our job postings analysis, here are some key areas of expertise to focus on: Technical Expertise Programming Languages: Proficiency in SQL (mentioned in 88% of job postings) and Python (78%) is essential. There you can build your skills in SQL, Python, data modeling, and basic networking.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Knowledge Hut

NOVEMBER 19, 2023

Open Source Support: Many Azure services support popular open-source frameworks like Apache Spark, Kafka, and Hadoop, providing flexibility for data engineering tasks. It offers three distinct environments: SQL for Databricks, Databricks Machine Learning for data engineering, and data science.

Data Engineer 52

Data Engineer Data Engineering Engineering PostgreSQL 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

Edureka

FEBRUARY 7, 2023

It is possible to use Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics. It can be set up as a security policy on all SQL Databases in an Azure subscription. Data entry into PDW is optimized by Polybase, which also supports T-SQL. For data access, Synapse SQL, an enhanced version of TSQL, is used.

Data Engineer 52

Data Engineer Data Engineering Engineering Hadoop 52

ProjectPro

MAY 19, 2015

It is possible today for organizations to store all the data generated by their business at an affordable price-all thanks to Hadoop, the Sirius star in the cluster of million stars. With Hadoop, even the impossible things look so trivial. So the big question is how is learning Hadoop helpful to you as an individual?

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

Monte Carlo

OCTOBER 31, 2024

Both traditional and AI data engineers should be fluent in SQL for managing structured data, but AI data engineers should be proficient in NoSQL databases as well for unstructured data management.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52