Apache NiFi
Apache NiFi is an open-source software with a data conversion framework for computerized data transfer between heterogeneous systems. It is intended to handle transactions involving data that transits between sources and destinations in a real-time mode for purposes of data analysis. NiFi has an easily portable and interactive GUI used for modelling the data flow and it possesses the data lineage, scalability, and security properties. They include Relational databases, Flat files, Text files, Syslog messages, Oracle AQs, MSMQ, TibCO, XML, and more.
Use Case:
One of the typical Apache NiFi deployment scenarios is the ingest of data in real-time together with storage in a data lake. For instance, a retail firm may employ NiFi in order to gather information from different data sources, including POS terminals, online purchases along inventory control mechanisms. NiFi is capable of processing this data in real-time and the data can be transformed to meet the required format before being moved to a data lake for excessive processing. This keeps the company informed on timely sales performance, inventory, customer compliance and sales trends, thus enhancing decision-making processes.
Case Study:
A healthcare organisation in this case used Apache NiFi to improve the handling of patient information which is originated from various sources like EHRs, lab outputs and wearable devices. Some of the issues that the organization encountered included a lack of integrated data structures or increased levels of data fragmentation where the various patients’ data were comprised of different format structures. This way, with the help of NiFi, they managed to create data flows that ensured the standardizing and enriching of the data and making all the data relevant to the works. It gave better data access to the clinicians so that they had better option availability to make better options and also increased the care of patients. In addition, data provenance in NiFi made it easier to trace these data lines thus meeting the data lineage compliance set by the law; HIPAA in this case.
Top Data Ingestion Tools for 2024
To capture data for utilising the informational value in today’s environment, the ingestion of data is of high importance to organisations. Data ingestion tools are especially helpful in this process and are responsible for transferring data from origin to storage and/or processing environments. As enterprises deliver more diverse data, the importance of the right ingestion tools becomes even more pronounced.
This guide focuses on the top data ingestion tools 2024 detailing the features, components, and fit for organization applications to help organizations make the right choice for their data architecture plan.
Table of Content
- Apache NiFi
- Apache Kafka
- AWS Glue
- Google Cloud Dataflow
- Microsoft Azure Data Factory
- StreamSets Data Collector
- Talend Data Integration
- Informatica Intelligent Cloud Services
- Matillion ETL
- Snowflake Data Cloud
- MongoDB Atlas Data Lake
- Talend Data Integration
- Azure Synapse Analytics
- IBM DataStage
- Alteryx