Nowadays, companies have lots of raw data stored in different systems, such as databases, data warehouses, and other systems across the enterprise. Processing raw data on Amazon Web Services (AWS) is one of the biggest challenges organizations face.
Experts at Clovertex recommend storing data on “Data Lake.” It is an excellent way to centralize and consolidate your company’s batch and streaming data assets into authoritative data for analytics.
It is important to unify your data in a data lake because it allows you to use machine learning algorithms and data analytics to efficiently process raw data. Research shows that companies that generate business value from raw data on AWS outperform their competitors.
AWS offers comprehensive, safe, and cost-effective services to organize and process raw data. These services are data migration, cloud infrastructure, analytics services, machine learning, and visualization tools. Read on!
Set Up Data Lake
Setting up Data Lake is essential for storing unstructured, raw data. You can use AWS Lake Formation to set up Data Lake. It enables you to easily create a secure Data Lake, allowing you to define where the raw data resides and what rules you want to apply.
Use AWS to collect, catalog, and transfer raw data into your Amazon S3 Data Lake. AWS allows for cleaning and classifying raw data using machine learning algorithms. Likewise, you can use AWS Glue to access your sensitive data and secure it properly.
Data Collection and Storage
AWS offers an excellent Data Lake solution to store and secure raw data. You can use AWS S3 to store your raw data and process it. Experts recommend AWS Glacier to keep archival information cost-effectively.
Use Kinesis Firehose delivery streams or AWS Import/Export Snowball to easily and quickly raw data into Amazon S3. AWS offers a wide range of features that help you reliable security to your Data Lake. It includes access control, policies, data transfer, logging, monitoring, etc.
Catalog and Search
If you want to perform effective raw data management, you can use services like Amazon ElasticSearch and DynamoDB to catalog and index your raw data in Amazon S3. AWS Lambda is a server-less feature that responds to events like uploading of new information. Amazon S3 can keep your data catalog up-to-date.
You can access and analyze the raw data stored in Amazon S3 quickly through Amazon EMR (Elastic MapReduce), Amazon Athena, Amazon Glue, Amazon Machine Learning, and Amazon RedShift. These tools allow you to scale and analyze your raw data efficiently. Examples include clickstream analytics, recommendation engines, fraud detection, internet of things (IoT) processing, and event-driven ETL.
You can use AWS services like Security Token Service (STS), Access Management (IAM), and Key Management Service (KMS) to secure your processed data. These tools also offer monitoring and auditing features to analyze your processed data.
You can extract and ingest raw data from online sources and on-premise systems using AWS Direct Connect. Use the AWS Database migration system for on-time load and Amazon Kinesis for real-time raw data storage and analysis.
Clovertex specializes in managing raw data storage and process. We can help create innovative Data Lake solutions on Amazon Web Services to enable you to govern your data and process it efficiently. Contact us today for raw data processing services.