Cloudera

SEPTEMBER 1, 2020

DDE is a new template flavor within CDP Data Hub in Cloudera’s public cloud deployment option (CDP PC). It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. data best served through Apache Solr). data best served through Apache Solr). What does DDE entail?

Cloud Storage 71

Cloud Storage Unstructured Data AWS Analytics Application 71

Cloudera

NOVEMBER 2, 2020

An AdTech company in the US provides processing, payment, and analytics services for digital advertisers. Data processing and analytics drive their entire business. In addition to understanding the attributes of an RTDW, it is useful to look at the types of applications that can be built within the RTDW category.

Data Warehouse 97

Data Warehouse Kafka Lambda Architecture Telecommunication 97

Striim

AUGUST 31, 2023

Showing how Kappa unifies batch and streaming pipelines The development of Kappa architecture has revolutionized data processing by allowing users to quickly and cost-effectively reduce data integration costs. Finally, kappa architectures are not suitable for all types of data processing tasks.

Data Integration 69

Data Integration Architecture Amazon Web Services Machine Learning 69

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Finnhub API with Kafka for Real-Time Financial Market Data Pipeline 3.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Workfall

JUNE 27, 2023

Commit Logs and Stream Processing: Kafka’s log-based storage and replayability make it ideal for stream processing use cases. Apache Kafka in Microservices Apache Kafka is an excellent choice for decoupled microservices architecture.

Kafka 75

Kafka Architecture AWS Transportation 75

Data Science Blog: Data Engineering

JULY 4, 2022

For fast analytic queries against another size of data, it uses in-memory caching and optimised query execution. It is a parallel processing framework for grouped computers to operate large-scale data analytics applications.

Hadoop 52

Hadoop Big Data Datasets Scala 52

Rockset

MAY 17, 2022

The tradeoff of these first-generation SQL-based big data systems was that they boosted data processing throughput at the expense of higher query latency. Hive implemented an SQL layer on Hadoop’s native MapReduce programming paradigm. As a result, the use cases remained firmly in batch mode.

SQL 52

SQL NoSQL Hadoop MongoDB 52

Edureka

AUGUST 23, 2024

For example, processed data can be stored in Amazon S3 for archival and batch processing, loaded into Amazon Redshift for data warehousing and complex queries, or indexed in Amazon Elasticsearch Service for full-text search and analytics. This supplies data to the applications waiting to use it.

AWS 52

AWS Kafka Amazon Web Services Medical 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

So whenever you hear that Process Mining can prepare RPA definitions you can expect that Task Mining is the real deal. An object-centric data model is a big deal because it offers the opportunity for a holistic approach and as a database a single source of truth for Process Mining but also for other types of analytical applications.

Architecture 52

Architecture Database-centric Process BI 52

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

JUNE 16, 2022

Use cases like fraud detection, network threat analysis, manufacturing intelligence, commerce optimization, real-time offers, instantaneous loan approvals, and more are now possible by moving the data processing components up the stream to address these real-time needs. .

Kafka 88

Kafka Manufacturing Data Lake SQL 88

Knowledge Hut

MAY 31, 2023

This platform provides a range of IoT tools and technologies to help developers build and manage IoT systems, including device management, data processing, and analytics. Data processing of large volumes of data including real-time data processing, storage, and analysis.

Programming Language 52

Programming Language Electronics Java Programming 52

Rockset

FEBRUARY 24, 2023

It has expanded to various industries and applications, including IoT sensor data, financial data, web analytics, gaming behavioral data, and many more use cases. It supports various data processing models such as stream and batch processing (both covered in part 2 of this series), and complex event processing.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

AltexSoft

OCTOBER 21, 2022

popular SQL and NoSQL database management systems including Oracle, SQL Server, Postgres, MySQL, MongoDB, Cassandra, and more; cloud storage services — Amazon S3, Azure Blob, and Google Cloud Storage; message brokers such as ActiveMQ, IBM MQ, and RabbitMQ; Big Data processing systems like Hadoop ; and. Kafka vs ETL.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

Edureka

JULY 3, 2024

Publish: Transformed data is then published either back to on-premises sources like SQL Server or kept in cloud storage. This makes the data ready for consumption by BI tools, analytics applications, or other systems. Manage Workflow: ADF manages these processes through time-sliced, scheduled pipelines.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

Knowledge Hut

MAY 3, 2024

Java does not support Read-Evaluate-Print-Loop (REPL), which is a major deal-breaker when choosing a programming language for big data processing. Python is one of the de-facto languages of Data Science. It’s popular for research, plotting, and data analysis. Support for ‘data science’ related work.

Scala 52

Scala Java Python Programming Language 52

U-Next

AUGUST 11, 2022

The next solution for self-service data analysis from Qlik is called Qlik Sense. It provides analytics features for different types of accounts, such as associated research and navigation, clever visualization, data preprocessing, and much more, making it one of the top BI tools. Zoho Analytics.

Business Intelligence 40

Business Intelligence BI Unstructured Data Programming 40

ProjectPro

SEPTEMBER 6, 2021

Popular instances where GCP is used widely are machine learning analytics, application modernization, security, and business collaboration. It is a serverless data integration service that makes data preparation easier, cheaper and faster.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

U-Next

AUGUST 26, 2022

This specific tool is frequently used for data processing, visualization, and polling. The R language should be respected, though, since it has several procedures built into it that are used to analyze statistical data. Additionally, anyone’s PC may quickly simply download the R language.

R (Programming) 52

R (Programming) Programming Language Algorithm Programming 52

ProjectPro

MAY 20, 2015

The company targets to deliver values to its customers through the free SaaS based analytics applications so that it can build credibility with the clients to encourage them to buy more. The products and services of Cloudera are changing the economics of big data analysis , BI, data processing and warehousing through Hadooponomics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Striim

NOVEMBER 8, 2023

A data mesh is technology-agnostic and underpins four main principles described in-depth in this blog post by Zhamak Dehghani. The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time.

Architecture 52

Architecture Generalist Government Datasets 52

Knowledge Hut

JULY 26, 2023

Cassandra specializes in handling high-volume, high-velocity, and high-reliability data, making it perfect for real-time data processing and fault tolerance applications. Apache Cassandra): Instead of the usual row-wise technique employed by relational databases, columnar databases store data in columns.

Database 52

Database NoSQL Telecommunication MongoDB 52

ProjectPro

MARCH 15, 2016

That way every server, stores a fragment of the entire data set and all such fragments are replicated on more than one server to achieve fault tolerance. Hadoop MapReduce MapReduce is a distributed data processing framework. Apache Hadoop provides solution to the problem caused by large volume of complex data.

Hadoop 40

Hadoop Retail Healthcare Banking 40

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. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. How to avoid the same.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

FEBRUARY 16, 2023

This entails managing data access, restricting data movement inside the warehouse, and SQL query optimization strategies. SQL enables engineers to perform data transformations within data warehouses, significantly accelerating data processing. are applied directly to the data in memory.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

phData: Data Engineering

JULY 18, 2023

Central Source of Truth for Analytics A Cloud Data Warehouse (CDW) is a type of database that provides analytical data processing and storage capabilities within a cloud-based infrastructure. Enter Snowflake The Snowflake Data Cloud is one of the most popular and powerful CDW providers.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

FEBRUARY 11, 2021

Translate the machine learning models defined by data scientists from environments like Python and R notebooks to analytic applications. 3) Machine Learning Engineer vs Data Scientist You might hear the terms data scientist and machine learning engineer used interchangeably but these are two different job roles.

Machine Learning 40

Machine Learning Engineering Programming Language Portfolio 40

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications.

Big Data 52

Big Data Coding Project Hadoop 52