Cloud1 data engineering solutions scale and cluster the databases, format and cleanse the data, handle and merge missing data and flatten it to make the data useful for analysis. Our clients include industry leaders from cybersecurity and entertainment domains as well as US Government agencies such as the National Women’s Business Bureau in Washington, DC. Voluminous and scattered data from legacy systems in multiple data formats is a nightmare for the data analyst. The difficulties are compounded by scalability issues. This complex scenario is oftentimes the reason for junking business intelligence plans. Cloud1 distributed microservices based data pipelines deployed in cloud have helped our clients handle scattered data from legacy systems and successfully establish business intelligence practices.

Cloud1 Data Engineering Service offerings

Data Lakes

A Data Lake provides your business with a massive, centralized database that contains all of your data. It enables you to perform big data queries that look across otherwise siloed data.
Cloud1 has a proven ability to build, operate and manage Data Lakes in the cloud, based on AWS best practices. Our recommended approach combines multiple AWS services into a complete solution:

● S3 for storage and Parquet as the file format
● AWS Glue for metadata management
● AWS Athena for big data query

Case Study

Cloud1 developed and managed a Data Lake to store data on movies in theaters for a leading market research firm. The solution enabled our customer to perform Big Data queries that would have been otherwise impossible as movies, theaters, and a large number of other necessary data were each stored in siloed databases. The key business value Cloud1 delivered was to enable queries and analyses that were otherwise impossible. The output of the analyses provided our customer with unique insights that they used to differentiate themselves in an otherwise crowded market.

Data pipelines

Pipelines are the preferred method to ingest, ETL and migrate streaming data. Cloud1 has a proven ability to develop scalable streaming data pipelines in the cloud. Our preferred tools and approach to pipelines follows
● Kafka (or AWS Kinesis)
●Microservices to create REST APIs for data ingest, producers to insert data into pipelines, consumers to read data from pipelines, and transformations to clean/normalize/validate/etc. data in transit.

Case Study

Cloud1 develops and operates multiple streaming data pipelines for a large Cyber Security company. The solution delivered by Cloud1 enables our customer to integrate with its ecosystem by ingesting large volumes of streaming data. Our solution provides the customer with an industry-leading integration capability that provides a unique competitive advantage. Our recommended solution was to ingest streaming data via Kinesis while handling batch data via traditional approaches.

Query-optimized Databases

Query-optimized databases help drive your user facing applications and are central to providing your customers with a high-quality user experience (UX). Cloud1 has a proven ability to develop scalable, low-latency solutions using a variety of different cloud-native databases:
● Cassandra (and DynamoDB)
● Elasticsearch
● Aurora (and RDS)

Case Study

Cloud1 developed and managed a large scale Aurora-based solution for a leading market research company. We managed everything from ETL and data ingestion to schema design and query optimization. The end result for our customers was a high-performance scalable solution that delighted their end users.

Cloud1 has extensive, hands on experience with the leading Data Engineering tools on the Market:
- Apache Hadoop
- Spark
- Kafka
- Mongo DB
- Cassandra
- Amazon web services