Do you know that Amazon Web Services (AWS) holds the top position, claiming a staggering 41.5% share of the cloud computing market – surpassing all their competitors combined (Microsoft Azure: 29.4%, Google Cloud: 3.0%, IBM: 2.6%)? With an amazing adoption rate of 85% in the enterprise segment and over 1 million active users spanning over 190 countries, AWS has solidified its position as the preferred platform for enterprises seeking to capitalize on cloud capabilities.
However, as a CEO, how can you effectively utilize this force to unlock your company’s data’s full potential? The answer is held by a secure and scalable data lake on AWS, with this blog post guiding you to navigate the process and understand how an AWS data lake can pivot your business towards success.
What Are the Features of AWS Data Lake?
- Controlled Exploration via Presigned URLs or IAM Roles: Data is shared, allowing for controlled exploration within S3.
- Managed Security: Get secure managed storage in S3, with at-rest encryption using KMS keys.
- Simplified Login (Optional): Allow federation sign-in through familiar SAML providers like Microsoft Active Directory Federation Services (AD FS).
- Power of Automation: Perform automation with the CLI or API integration into existing workflows.
- Easy UI Use: Through the web-based console, perform all tasks from managing users and policies to creating data packages and then analysis manifests.
Why AWS for your Data Lake?
- Unmatched Scale and Resources
AWS has deployed more cloud infrastructure than the next 14 competitors combined – 5 times more. Even more impressive is the fact that AWS continues to expand; it lays down as much infrastructure every day as it was running just 7 years ago. This thus ensures seamless growth of your data lake with increasing volumes of data.
- Cost Efficiency
Setting up a data lake, let alone maintaining one, is an enormous undertaking. AWS gets it. As if to prove the point of being wallet-friendly, AWS has dropped prices 67 times since the debut of the platform in 2006. In addition, compared to the next largest cloud provider, AWS delivers up to 45% more price-to-performance ratio on equal infrastructure – directly to your bottom line.
- Rock-solid Security and Compliance
The general concerns are that, more so with sensitive information, data security is paramount. At AWS, security is ranked as the number one priority with a comprehensive suite of 143 security standards and compliance certifications, many of which are industry-recognized accreditations such as PCI-DSS, HIPAA/HITECH, FedRAMP, GDPR, FIPS 140-2, NIST 800-171, among others.
- Global Reach
AWS provides you with an ocean of opportunity to build out your data lake. With over 1 million active users in 190 countries, AWS really is a global infrastructure. Data centers, whose strategic positioning cuts across the United States, Canada, Europe, Asia, South America, and Australia, ensure low latency and data residency compliance no matter where you are in the world.
How to Build Your Data Lake on AWS?
- Define Your Data Lake Strategy
The first step of creating your data lake on AWS is a clearly defined strategy; identification of all data sources and the type of data that is to be leveraged: structured database records, unstructured documents, or media files. You will then define your needs for data ingestion and data processing against parameters such as data volume, velocity, and variety. Across your deployment, early setup of requirements pertaining to data governance and security is important for sustaining compliance with related regulations and protecting sensitive information. Finally, clearly define what you are trying to achieve with your data lake. You can set it to achieve better business intelligence, allow advanced analytics, or support machine learning initiatives.
- Set Up Your Aws Foundation
With your strategy in place, your next step is laying an AWS foundation. First of all, if you are new to AWS services, create an account on AWS. Next, you will configure your Virtual Private Cloud (VPC), a private section of the AWS cloud in which you can launch your resources within your defined virtual network. You need to create Identity and Access Management (IAM) roles and policies to set up who can use your data lake resources and for what purposes. You should also implement security features such as encryption, network security groups, and access logging in order to protect your data to the fullest extent possible while also ensuring compliance.
- Choose and Implement AWS Services
AWS has a rich ecosystem of services for building a robust data lake. Start with Amazon S3 as the primary storage layer for scalable, durable, cost-effective object storage. Implement AWS Glue for data cataloging and the ETL process in order to discover, prepare, and combine data for analytics. Set up Amazon Athena to ad hoc SQL-based query your data directly in S3. Consider Amazon Redshift in the case of data warehousing requirements. Use Amazon EMR (previously called Amazon Elastic MapReduce), for big data processing, supporting frameworks like Apache Spark and Hive.
- Develop Data Ingestion and Analysis Workflows
The final step is to develop data ingestion and analysis workflows. Design data ingestion pipelines with AWS Glue or AWS Data Pipeline that automate bringing data into your lake from several sources. Apply data transformation jobs for cleansing, normalizing, and enriching your data during its ingression into the lake. Put in place data quality checks and monitoring to guarantee data integrity and reliability. Finally, create analytics processes using services like Amazon QuickSight for easier visualization or integration with the BI tools of your choice.
What Are Some Considerations for CEOs?
- Ensure the Data Lake Initiative Aligns with the Overall Business Strategy
CEOs must ensure that the data lake project aligns with crucial business objectives. This entails determining how the data lake will propel value, enhance decision-making, and bolster competitive edge.
- Understand Total Cost of Ownership (TCO)
Executives must understand the complete monetary ramifications of implementing a data lake, encompassing initial establishment expenditures, continual operational costs, potential cost-effectiveness through enhanced proficiency, and the ROI derived from data-informed insights.
- Assess and Plan for Necessary Changes in Processes and Workflows
The implementation of a data lake frequently necessitates organizational modifications. To maximize the potential of new data capabilities, CEOs must anticipate and strategize for changes in data governance, team compositions, and business procedures.
- Scalability and Future-proofing
It is essential for CEOs to guarantee the scalability of the data lake solution in accordance with the evolving demands of the company. This task requires making strategic decisions regarding adaptable technologies, anticipating potential forthcoming data sources, and preparing for heightened data volumes and increasingly intricate analytical needs.
Conclusion
In the business world that relies on data today, constructing a strong data lake on AWS could be a big advantage for your company. As a CEO, knowing these important points – from aligning with the business plan to securing future value – would be very essential. AWS has unmatched standing in the market, is cost-effective, ensures security, and offers worldwide coverage which makes it perfect for developing your data lake.
Are you prepared to unleash your data’s potential using an AWS data lake? Ascentt’s managed services and support are essential elements for the success of any technology platform or solution. We provide complete managed services as well as support services in all our practice areas, aiding our clients to make full use of their technology investment. To begin the process of AWS data lake implementation, contact us now. Let Ascentt assist you in making the most of your AWS potential for data lakes, from start to finish.