Develop a Secure Data Lake in a Few Days
Modern Data Platform Services
Your Cloud Becomes an Efficient Data Warehouse
In the age of digitization and Internet of things the mass of data continiously increases. The challenge lies in the complexity of making mass data available for further usage, gaining insights from it and deriving actions to generate sustainable business value. The good news is that this challenge can be met.
In the cloud, companies can find a storage location that can scale flexibly and cost-effectively in parallel with the growth in data volumes. A data lake in the public cloud, as a centralized, managed and secure repository, can store data cost-effectively, whether in its original form or prepared for further analysis and use. This centralized data repository replaces decentralized data silos and allows data to be combined for different types of analysis to gain insight and make better business decisions.
Advantages
With the Right Partner, It's Quick and Easy to Get to Data Lake in AWS
Benefit from our experience and proven best practices in building your Data Lake in AWS. We help you collect, store, and prepare your data for further use in Amazon Redshift, the data warehouse in AWS, using other AWS services such as Amazon DynamoDB, Amazon EMR, Ama-zon Kinesis Firehose, and Amazon S3, and enable you to apply various types of analytics such as SQL queries, big data analytics, full-text search, real-time analytics, and machine learning.
- On-premise data movements
- Real-time data movements
- Implementation of ETL processes
- Development of a RedShift Data Warehouse Cluster
- Modelling of data warehouse data models according to best practices
- Development and implementation of Kinesis / data pipeline
- Implementation of machine learning services
Knowledge Advantage Through Data
Gain knowledge from more data from multiple sources in the shortest possible time and enable better and faster decision making.
Improved Customer Interaction
Combine customer data from your CRM with e.g. social media analytics through your data lake and discover the most profitable customer clusters, the cause of customer churn and gain insight into the effectiveness of promotions.
Research Lead
Research and development hypotheses can be tested, assumptions refined and results evaluated.
Increase Operational Efficiency
A data lake makes it easy to store and analyze machine-generated IoT data to find ways to reduce operating costs and improve quality.
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