Data Engineering and Big Data technologies
- Kafka
- Spark
- Hadoop
- GoLang
- Java
- PostgreSQL
- Scala
- Beam
- Apache Airflow
- Elasticsearch
- Redis
- InfluxDB
- MongoDB
- Parquet
- ORC
- NiFi
- MinIO
- EventStore DB
- Submarine
- Atlas
- Hive
- Pig
- Casandra
- AWS kinesis
- Fluentd
- HBase
- Loud ML
- Ckan
- BigQuery
- DataFlow
- Neo4j
- Ignite
- Debezium
- Amundsen
- Camel
analysis
A peek into our Data Engineering practices
- A guided practice of DataOps
Following DataOps best practices and encouraging the use of workflow orchestrators and collaboration tools around data is key to delivering business value while cutting down costs of data operations at the same time.
- Streams over Batches
Whenever possible we prefer to use streams over batch processing of large data sets while using certain techniques & tools to rollback and correct and alter faulty data before they impact downstream processors.
- Visualising using Data Maps
We implement visualizations and data maps that allow us to automatically detect and manage data drift, alert users to any issues and uncover pitfalls and improve on the used data architecture as early as possible.
The Significant benefits of automating Data Lineage
As a business grows, so does data, along with the need to manage it across the multiple silos of the organization. Recent researches show that on average, businesses need to increases their data storage capacity by 60 percent every year.
The vast amount of data generated by clients, daily business operations and transactions comes with a huge host of problems. Extreme amounts of data redundancy, as well as process and technology redundancy makes it impossible to manage data across an organization, and that's where Automated Data lineage comes into play.
Automated data lineage connects the dots as it systematically ingests metadata from multiple data sources, and curates it to build data catalogs which helps maintain data quality, avoid redundancy and guides the building of metrics and access policies around data.
It also helps a business remain compliant with multiple regulatory frameworks such as the GDPR and California Consumer Privacy Act (CCPA).
Making tech teams lives easier
Behind every great product there are great teams and interesting experiences to be shared and stories to be told. That's why listening to our engineers is on top of our internal communication practices at Area99.
We take the inspiration and ideas from our engineers to build software quality and automation tools and set standards that make the creation of new products an exciting journey for everyone.
