ProjectPro

JUNE 6, 2025

Apache NiFi Apache NiFi is a commonly used open-source data integration tool for data routing, transformation, and system mediation. NiFi's user-friendly interface allows users to design complex data flows effortlessly, making it an excellent choice for data ingestion and routing tasks.

Data Pipeline 40

Data Pipeline Building Retail Data Ingestion 40

Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Kafka 52

ProjectPro

JUNE 6, 2025

With global data creation expected to soar past 180 zettabytes by 2025, businesses face an immense challenge: managing, storing, and extracting value from this explosion of information. Traditional data storage systems like data warehouses were designed to handle structured and preprocessed data.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Supports big data technology well. Supports high availability for data storage. Supports uniform consistency of data throughout different locations. The more you use the product, the cheaper the subscription plans. Support large-scale implementation of machine learning algorithms. Similar pricing as AWS.

Data Engineering 94

Data Engineering Data Engineer Engineering Amazon Web Services 94

Knowledge Hut

JULY 3, 2023

This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing. This refers to Real-time data ingestion. To achieve this goal, pursuing Data Engineer certification can be highly beneficial.

Data Ingestion 52

Data Ingestion Pipeline-centric Google Cloud Media 52

phData: Data Engineering

FEBRUARY 21, 2025

Prior to making a decision, an organization must consider the Total Cost of Ownership (TCO) for each potential data warehousing solution. On the other hand, cloud data warehouses can scale seamlessly. Vertical scaling refers to the increase in capability of existing computational resources, including CPU, RAM, or storage capacity.

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics. Contact phData Today!

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

Key Concepts Involved in Azure Data Factory Pipeline Activity Datasets Data Flows Parameters Control Flow Linked Services Triggers Integration Runtime (IR) Top Azure Data Factory Use Cases Data Integration Data Reservoir for Product Recommendations How to Build an Azure Data Factory pipeline?

Data Engineering 40

Data Engineering Data Engineer Engineering Hospitality 40

ProjectPro

JUNE 6, 2025

Data Warehouse The Data Warehouse component offers industry-leading SQL performance and scalability by fully separating compute from storage. This allows independent scaling of both components and native data storage in the open Delta Lake format.

Database-centric 40

Database-centric BI Pipeline-centric Data Lake 40

ProjectPro

JUNE 6, 2025

These AWS resources offer the highest level of usability and are created specifically for the performance optimization of various applications using content delivery features, data storage, and other methods. Table of Contents Why Learn AWS for Data Engineering? What is Data Engineering?? What is AWS for Data Engineering?

AWS 40

AWS Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

ETL is a process that involves data extraction, transformation, and loading from multiple sources to a data warehouse, data lake, or another centralized data repository. An ETL developer designs, builds and manages data storage systems while ensuring they have important data for the business.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Using familiar SQL as Athena queries on raw data stored in S3 is easy; that is an important point, and you will explore real-world examples related to this in the latter part of the blog. It is compatible with Amazon S3 when it comes to data storage data as there is no requirement for any other storage mechanism to run the queries.

AWS 67

AWS Big Data SQL Datasets 67

ProjectPro

JUNE 6, 2025

This certification attests to your proficiency in building scalable and efficient data pipelines , understanding the principles of data security, and optimizing performance for diverse analytics workloads. Why Should You Get AWS Data Engineer Associate Certification?

AWS 40

AWS Certification Data Engineering Data Engineer 40

ProjectPro

JUNE 6, 2025

AWS Data Engineering is one of the core elements of AWS Cloud in delivering the ultimate solution to users. AWS Data Engineering helps big data professionals manage Data Pipelines, Data Transfer, and Data Storage. Table of Contents Who is an AWS Data Engineer? What Does an AWS Data Engineer Do?

AWS 45

AWS Data Engineering Data Engineer Amazon Web Services 45

ProjectPro

JUNE 6, 2025

Apache Kafka offers a robust solution for permanent data storage in a distributed, durable, and fault-tolerant cluster. This ensures that streams of data are not only processed efficiently but also stored securely. Kafka's distributed architecture enables seamless scalability by allowing the addition of new nodes to the cluster.

Data Pipeline 49

Data Pipeline Google Cloud AWS Kafka 49

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 108

Data Lake Data Ingestion Bytes Cloud Computing 108

ProjectPro

JUNE 6, 2025

An ETL (Extract, Transform, Load) Data Engineer is responsible for designing, building, and maintaining the systems that extract data from various sources, transform it into a format suitable for data analysis, and load it into data warehouses, lakes, or other data storage systems.

Data Engineering 40

Data Engineering Data Engineer ETL Tools Engineering 40

ProjectPro

JUNE 6, 2025

Setting up the cloud to store data to ensure high availability is one of the most critical tasks for big data specialists. Due to this, knowledge of cloud computing platforms and tools is now essential for data engineers working with big data.

Data Engineering 40

Data Engineering Data Engineer PostgreSQL Engineering 40

ProjectPro

JUNE 6, 2025

The Azure DP 203 certification equips you with the skills and knowledge needed to navigate the Azure data ecosystem with confidence and expertise. This certification validates your ability to design and implement Microsoft Azure data storage solutions. Table of Contents Why Enroll for DP 203: Data Engineering on Microsoft Azure?

Certification 40

Certification Data Storage Big Data Data Engineering 40

Cloudera

NOVEMBER 1, 2023

The connector makes it easy to update the LLM context by loading, chunking, generating embeddings, and inserting them into the Pinecone database as soon as new data is available. High-level overview of real-time data ingest with Cloudera DataFlow to Pinecone vector database.

Machine Learning 110

Machine Learning Data Ingestion Database Architecture 110

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive.

Manufacturing 108

Manufacturing Machine Learning Electronics Data Ingestion 108

Snowflake

NOVEMBER 29, 2023

For example, the data storage systems and processing pipelines that capture information from genomic sequencing instruments are very different from those that capture the clinical characteristics of a patient from a site. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 114

Metadata Healthcare Medical Data Storage 114

ProjectPro

JUNE 6, 2025

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

They ensure the data flows smoothly and is prepared for analysis. Apache Hadoop Development and Implementation Big Data Developers often work extensively with Apache Hadoop , a widely used distributed data storage and processing framework. Apache Kafka: Kafka is a distributed event streaming platform.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Explore Data Engineer Projects to Learn the Plumbing of Data Science Role and Responsibilities of a Data Engineer Prepare, handle, and supervise efficient data pipeline architectures. Build and deploy ETL/ELT data pipelines that can begin with data ingestion and complete various data-related tasks.

Data Engineering 58

Data Engineering Data Engineer Engineering Amazon Web Services 58

ProjectPro

JUNE 6, 2025

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 40

Big Data Hadoop Relational Database AWS 40

Lyft Engineering

NOVEMBER 29, 2023

Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data. Druid enables low latency (real-time) data ingestion, flexible data exploration and fast data aggregation resulting in sub-second query latencies.

Kafka 109

Kafka Data Ingestion Architecture Datasets 109

ProjectPro

JUNE 6, 2025

Data engineering tools are specialized applications that make building data pipelines and designing algorithms easier and more efficient. These tools are responsible for making the day-to-day tasks of a data engineer easier in various ways. AWS, Azure, GCP , etc., are some of the popular cloud platforms.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Once the data is ready, you will use AWS SageMaker to build a model that recommends products to users based on their previous purchases and browsing history. The collected data should then be cleaned and preprocessed to remove noise and inconsistencies. Next, you will choose an appropriate anomaly detection algorithm.

AWS 61

AWS Project Medical Datasets 61

ProjectPro

JUNE 6, 2025

Let us compare traditional data warehousing and Hadoop-based BI solutions to better understand how using BI on Hadoop proves more effective than traditional data warehousing- Point Of Comparison Traditional Data Warehousing BI On Hadoop Solutions Data Storage Structured data in relational databases.

Hadoop 40

Hadoop BI Big Data Business Intelligence 40

Christophe Blefari

JANUARY 20, 2024

formats — This is a huge part of data engineering. Picking the right format for your data storage. The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. workflows (Airflow, Prefect, Dagster, etc.)

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

ProjectPro

JUNE 6, 2025

Azure Stack Familiarize yourself with core Microsoft Azure data services such as Azure Data Lake, Azure Synapse, Azure Data Factory , Azure Cosmos DB, etc. Further, you will read the Data tags from Databricks into Spark and display the results in a bar chart. Describe ways to represent data.

Certification 45

Certification Google Cloud Data Lake SQL 45

ProjectPro

JUNE 6, 2025

One of the leading cloud service providers, Amazon Web Services (AWS ), offers powerful tools and services that can propel your data analysis endeavors to new heights. With AWS, you gain access to scalable infrastructure, robust data storage, and cutting-edge analytics capabilities.

AWS 52

AWS Certification Data Analytics Big Data 52

ProjectPro

JUNE 6, 2025

Concepts such as data modeling , ETL (Extract, Transform, Load) processes, and data storage in a warehouse environment will be helpful for beginners who are willing to learn Snowflake Datawarehouse. You must understand the importance of file formats, staging areas, and data ingestion techniques.

Data Warehouse 40

Data Warehouse SQL AWS Big Data 40

Cloudera

AUGUST 27, 2021

The organization was locked into a legacy data warehouse with high operational costs and inability to perform exploratory analytics. With more than 25TB of data ingested from over 200 different sources, Telkomsel recognized that to best serve its customers it had to get to grips with its data. .

Telecommunication 85

Telecommunication Transportation Big Data Data Ingestion 85

ProjectPro

JUNE 6, 2025

Smooth Integration with other AWS tools AWS Glue is relatively simple to integrate with data sources and targets like Amazon Kinesis , Amazon Redshift, Amazon S3, and Amazon MSK. It is also compatible with other popular data storage that may be deployed on Amazon EC2 instances.

AWS 66

AWS Scala Metadata Data Lake 66