ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDD uses a key to partition data into smaller chunks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

LinkedIn Engineering

DECEMBER 20, 2023

Collecting signals is not just about quantity; it's about ensuring the diversity and quality of the data, and ensuring that the data is relevant, accurate, and reflective of the real-world activities of the member. We need systems to ingest, process, and analyze the data efficiently. Espresso , Venice , Rest.li

Building 91

Building Algorithm Kafka Machine Learning 91

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. In the event that they are not the same, what are the difference s? To provide meaningful business insights, it collects and manages data from a variety of sources. Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

SEPTEMBER 21, 2023

It interacts through comprehensive REST APIs , processing and returning results in JSON format. ESRE enables advanced relevance ranking, natural language processing (NLP), and the ability to work with large language models (LLMs) like OpenAI’s GPT-3 and GPT-4. Analysis of logs, metrics, and security events.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

NOVEMBER 15, 2021

It derives its name “Beam” which is from “Batch” + “Stream” from its functionalities for both batch and streaming the parallel processing pipelines for data. You can contribute to Apache Beam open-source big data project here: [link] 2.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JUNE 28, 2016

Apache Kafka is breaking barriers and eliminating the slow batch processing method that is used by Hadoop. Kafka was mainly developed to make working with Hadoop easier. True that it is eliminating the limitations of Hadoop – but it will not eliminate Hadoop itself.

Kafka 40

Kafka Systems Hadoop BI 40

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

phData: Data Engineering

JANUARY 3, 2022

The best option will vary depending on whether your data is structured or unstructured (or even semi-structured), normalized or denormalized, and whether you need data in a row or columnar data format. Is your data key/value-based? Are there complex relationships between the data? Data must also be performant.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Cloudera

NOVEMBER 13, 2020

Apache Impala is synonymous with high-performance processing of extremely large datasets, but what if our data isn’t huge? It turns out that Apache Impala scales down with data just as well as it scales up. For a more in-depth description of these phases please refer to Impala: A Modern, Open-Source SQL Engine for Hadoop.

Metadata 142

Metadata Coding SQL Database 142

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

APRIL 15, 2022

It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. It’s probably because their analytics database lacks the features necessary to deliver data-driven decisions accurately in real time. Transmitting out-of-order data is not the issue.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52