E-book: 10 key considerations to build a sustainable and robust data lake on the cloud
Reports reveal that the data lakes market is growing at a CAGR of 27.8% and is expected to touch an aggregate of $12.01 billion by 2024. To tap the unmatched agility, scalability, and advanced capabilities of the cloud, enterprises across the globe are considering the move to cloud-based data lakes. Cloud-based data lakes help them avoid upfront hardware investments for complex computing and analytics, discover new information models, and have diverse query capabilities, which is why they are gaining popularity.
However, there are challenges like lack of long-term data governance, lack of proper data architecture, lack of planning, and funding and cost while adopting a data lake on the cloud. To address these challenges, enterprises need to align all stakeholders to common goals, ensure strategic planning, and make smarter technology choices to ensure successful cloud transformation.
But what are the critical levers of success in this journey of transformation? The 10 key considerations to build a sustainable and robust data lake on the cloud are as follows:
1. Manage organizational change: Different people within the organization have different objectives and needs. Therefore, it is essential to understand, align, and address the needs of various stakeholders to have a common enterprise goal. It is important to understand the enterprise data strategy and align with the security, compliance, and governance needs to build a robust, sustainable, and secure data lake.
2. Ensure value: Once the goals are aligned, it is crucial to prioritize your cloud adoption strategy to ensure it adds value to the organization from day one.
3. Focus on building foundational capabilities: Enterprises tend to focus on building core functionalities and de-prioritize the important non-functional aspects. While building a data lake on the cloud, focus on building foundational capabilities and extending them as a part of the overall governance model.
4. Identify the right tools: Perform an exhaustive assessment to identify all the capabilities and tools required for an end-to-end solution.
5. Validate the goals: The key to a successful data lake on the cloud is to start small. Have SMART (specific, measurable, attainable, relevant, and time-based) goals, perform a proof-of-concept before implementation, and extend it once the POC is successful. It will help you recover fast in case of failure, assess, and measure success, and make changes quickly without disrupting business.
6. Avoid vendor lock-ins: Assess the level and layer of lock-ins before choosing a cloud provider. Ask questions to decide and devise a futuristic strategy before you select which layer to lock in — tool, framework, platform, cloud, or solution.
7. Plan for business expansion: Choose a cloud vendor and develop a strategy that is scalable and designed to meet your business expansion goals. Consider the geographical compliances of the new territories that you plan to explore and ensure the platform can integrate with other tools and platforms to address future use cases. For example, expanding operations from the US to Europe would require reconsidering compliance strategies.
8. Embrace speed: Enterprises are moving their data lakes to the cloud to embrace speed and agility. To maintain the pace of development and speed of delivery that comes with the cloud, enterprises need to invest in DevOps.
9. Calculate ROI and TCO accurately: While planning the migration, enterprises often ignore hidden costs. To calculate and optimize the total cost of ownership (TCO), take all expenses into account.
10. Measure key metrics: Apart from expenditure, it is also important to assess other metrics and configure all the necessary parameters for measurement.
Download the e-book to explore the critical levers of success in this journey of transformation to help decision-makers overcome challenges and adopt the right strategy needed to create a sustainable, robust data lake on the cloud.
