Christophe Blefari

DECEMBER 31, 2023

LLMs for builders: jargons, theory & history — Mehdi, compiled in a large article all the necessary vocab to understand the basic conversation when it comes to generative. They released their first AI endpoints : generative and embedding. There is a great article with an image generation from a sketch.

Data 100

Data Cloud Storage Datasets Python 100

Knowledge Hut

DECEMBER 26, 2023

Programming is at the core of software development, which is why there is a huge demand for programmers—a demand that is growing exponentially and is expected to rise at a steady rate even in the future. Also, read about what is markdown and, why should we use it.

Certification 98

Certification Programming MongoDB R (Programming) 98

Cloudera

AUGUST 3, 2022

Fine grained access control (FGAC) with Spark. The challenges of arbitrary code execution notwithstanding, there have been attempts to provide a stronger security model but with mixed results. One approach is to use 3rd party tools (such as Privacera ) that integrate with Spark. Introducing Spark Secure Access Mode.

Datasets 85

Datasets BI Machine Learning Accessible 85

ProjectPro

FEBRUARY 8, 2023

Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

MARCH 27, 2024

A global data explosion is generating almost 2.5 Why Is Big Data Analytics Important? Apache Spark. Apache Storm. Apache SAMOA. APACHE Hadoop Big data is being processed and stored using this Java-based open-source platform, and data can be processed efficiently and in parallel thanks to the cluster system.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Data Engineering Podcast

JANUARY 15, 2022

Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud. Prophecy provides an easy-to-use visual interface to design & deploy data pipelines on Apache Spark & Apache Airflow. And don’t forget to thank them for their continued support of this show!

Engineering 100

Engineering Electronics ETL Tools Data Pipeline 100

ProjectPro

JANUARY 25, 2022

Did you know that, according to Linkedin, over 24,000 Big Data jobs in the US list Apache Spark as a required skill? Learning Spark has become more of a necessity to enter the Big Data industry. Apache Spark is one of the most popular frameworks for managing and dealing with Big Data. Why use PySpark?

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. Why are Hadoop Big Data Tools Needed? HDFS HDFS is the abbreviated form of Hadoop Distributed File System and is a component of Apache Hadoop.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Cloudera

JULY 18, 2022

In part 1 of this blog we discussed how Cloudera DataFlow for the Public Cloud (CDF-PC), the universal data distribution service powered by Apache NiFi, can make it easy to acquire data from wherever it originates and move it efficiently to make it available to other applications in a streaming fashion. Apache Flink. Use case recap.

Process 86

Process Kafka Scala SQL 86

Towards Data Science

NOVEMBER 4, 2023

In this case, SQL stops being an option in many cases making it difficult to query the data for those users who are not familiar with programming. I previously wrote about it in one of my stories on Apache Iceberg table format [2]. This would be the right way to go for data analyst teams that are not familiar with coding.

Data Engineering 86

Data Engineering Data Engineer Engineering BI 86

ProjectPro

NOVEMBER 22, 2021

During the development phase, the team agreed on a blend of PyCharm for developing code and Jupyter for interactively running the code. PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 31, 2023

Big data analytics analyzes structured and unstructured data to generate meaningful insights based on changing market trends, hidden patterns, and correlations. Value: Value refers to deriving valuable insights to meet business needs and generate revenues. FSCK generates a summary report that covers the file system's overall health.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Data Engineering Podcast

DECEMBER 18, 2022

Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. or any other destination you choose. Pricing for SQLake is simple.

Data Lake 100

Data Lake Data Warehouse Data Pipeline MongoDB 100

Data Engineering Weekly

NOVEMBER 27, 2022

“Developer’s Job is to ship the application code, not to make your dashboard looks good” I agree that shipping the application code is the priority. But What is an “Application Code”? The real-time agent assistant model is an exciting read. I want to address one comment in the conversation.

Data Engineering 52

Data Engineering Data Engineer Engineering SQL 52

Monte Carlo

MAY 31, 2022

Field-level data lineage (not necessarily Spark lineage) with hundreds of connections between objects in upstream and downstream tables. for SQL based transformations, but some of the most popular, Spark-based systems remained a blindspot for us and for the industry at large. Easy compared to Spark lineage? Absolutely.

Data Lake 52

Data Lake Building Scala Metadata 52

ProjectPro

FEBRUARY 18, 2022

Let us now understand why the ETL pipelines hold such great value in Data Science and Analytics. Table of Contents Why is ETL used in Data Science? Why is ETL used in Data Science? In real-time, the ETL pipeline gathers data from two sources, joins relevant records from each stream, enhances the output, and generates an average.

Project 52

Project AWS Kafka Healthcare 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Be sure to read to the end where we share 6 data pipeline architecture diagrams used by real data teams at companies like JetBlue, Fox Networks, Drata, and more. Why is data pipeline architecture important? What is data pipeline architecture?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Towards Data Science

JULY 24, 2023

Read on to see where that might be. Why are these things related, and more importantly, why should data leaders care? Let’s dive into the current landscape and recent evolutions before looking closer at why that may be the case. The Storage & Compute Data Platform Spectrum Image courtesy of the author.

Metadata 97

Metadata Data Warehouse Data Lake Data Science 97

Big Data Tools

OCTOBER 5, 2021

Zingg is a tool that integrates with Spark and tries to answer this question automatically, without the quadratic complexity of the task! Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 Hudi 0.9 – This release adds something huge: Spark DDL and DML support (experimental).

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Big Data Tools

OCTOBER 5, 2021

Zingg is a tool that integrates with Spark and tries to answer this question automatically, without the quadratic complexity of the task! Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 Hudi 0.9 – This release adds something huge: Spark DDL and DML support (experimental).

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

ProjectPro

JUNE 18, 2021

Why do data scientists prefer Python over Java? Why do data scientists love Python for Data Science? Netflix and Spotify use Python to generate their recommendation engines. Why do data scientists love Python for Data Science? Java vs Python for Data Science- Which is better? renamed to Java.

Java 52

Java Data Science Python Programming Language 52

ProjectPro

AUGUST 24, 2021

. :) But before you start data engineering project ideas list, read the next section to know what your checklist for prepping for data engineering role should look like and why. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rock the JVM

FEBRUARY 5, 2023

Enter Giannis: Flink SQL is a powerful high level API for running queries on streaming (and batch) datasets. Streaming (and Batch) SQL 1.1 Batch SQL Queries operate on static data, i.e. on data stored on disk, already available and the results are considered complete. bin/sql-client.sh This is called a Dynamic Table.

SQL 63

SQL Kafka Metadata Database 63

Rockset

APRIL 15, 2022

This is the second post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. So why are their analytics still crawling through in batches instead of real time? One method used by Snowflake, Apache Druid and others is called copy-on-write.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

ProjectPro

MAY 31, 2021

However, before moving on to a list of big data project ideas worth exploring and adding to your portfolio, let us first get a clear picture of what big data is and why everyone is interested in it. Recommendations can also be generated based on patterns in a given area or based on age groups, sex, and other similar interests.

Big Data 52

Big Data Coding Project Hadoop 52

Rockset

MAY 12, 2022

This is the third post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. Why Bursty Data Traffic Is an Issue Today These conditions have completely flipped. However, these databases tend to sacrifice support for complex SQL queries at any scale.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Electronics 52

Rockset

MARCH 10, 2022

This is the first post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. He was also a contributor to the open source Apache HBase project. A platform such as Apache Kafka/Confluent , Spark or Amazon Kinesis for publishing that stream of event data.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 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. And that ability to cost-effectively reach hyperscale is why these solutions are some of the fastest growing in the world. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

ProjectPro

NOVEMBER 30, 2021

Join Tables: If our source is RDBMS or SQL tables, we might need to join or merge multiple data tables. For example, address data may have misspelled street names, incorrect zip codes, etc., or mobile numbers may have special symbols and country codes appended before them. Nevertheless, this is an optional step that we can omit.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

NOVEMBER 6, 2015

Apache Hive was introduced by Facebook to manage and process the large datasets in the distributed storage in Hadoop. Apache Hive is an abstraction on Hadoop MapReduce and has its own SQL like language HiveQL. Cloudera Impala was developed to resolve the limitations posed by the low interaction of Hadoop Sql.

Hadoop 52

Hadoop SQL Java Metadata 52

ProjectPro

JUNE 24, 2021

Table of Contents Skills Required for Data Analytics Jobs Why Should Students Work on Big Data Analytics Projects ? 10+ Real-Time Azure Project Ideas for Beginners to Practice Access Job Recommendation System Project with Source Code Why Should Students Work on Big Data Analytics Projects ?

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

JANUARY 31, 2022

This is the reason why we need Data Warehouses. Snowflake is a Data Warehouse solution that supports ANSI SQL and is available as a SaaS (Software-as-a-Service). On the other hand, Snowflake integrates an entirely new SQL query engine with unique cloud-native architecture. What is Snowflake Data Warehouse?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 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. Why Apache Spark?

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

DECEMBER 10, 2021

Table of Contents Why Must You Prepare For Azure Interview Questions? Why is Azure Diagnostics API needed? Why Must You Prepare For Azure Interview Questions? It can handle massive numbers of application requests by storing highly trafficked data in server memory, where it can be written to and read fast.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

JULY 27, 2021

Why is Data Engineering In Demand? 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. E.g. PostgreSQL, MySQL, Oracle, Microsoft SQL Server.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 11, 2014

Confused over which framework to choose for big data processing - Hadoop MapReduce vs. Apache Spark. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

Hadoop 40

Hadoop Scala Machine Learning Java 40

ProjectPro

JUNE 29, 2021

Your search for Apache Kafka interview questions ends right here! Let us now dive directly into the Apache Kafka interview questions and answers and help you get started with your Big Data interview preparation! What are the best Apache Kafka interview questions and answers for experienced? What are topics in Apache Kafka?

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Kafka Bytes Big Data Java 40