Data as An Asset

Data governance is the process of managing the availability, usability, integrity, and security of data in organization's. It ensures that data is consistent, accurate, secure, and compliant with regulations.

Data Governance is crucial for businesses as it ensures proper handling of data which includes access, usage, and management. Important aspects to look for: Data Quality Improvement Regulatory Compliance Risk Management Operational Efficiency Enhanced Decision-Making Data Governance is key for maintaining high-quality data. It helps in establishing clear protocols that enhance the accuracy and reliability of data used in decision-making processes. This is important for businesses striving to gain a competitive edge in data-driven strategies. Companies can reduce errors and improve the overall effectiveness of their data analytics as they have consistent, accurate, and timely data to guide business operations.Data Governance also plays a vital role in ensuring regulatory compliance. With strict regulations like GDPR and CCPA, businesses must adhere to guidelines on data protection and privacy. Effective Data Governance frameworks help organizations ensure compliance, minimizing the risks of legal penalties and reputational damage. By fostering a culture of accountability, Data Governance ensures employees are aware of their roles in data management, thus enhancing operational efficiency and safeguarding sensitive information.

AWS Lambda is probably the most mature serverless platform available today due to the amount of time it has been operating. It has proven to be reliable and is capable of handling workloads of various sizes. AWS Lambda offers features beyond the basics that can be expected from every serverless provider. The service has become more flexible and powerful as time passes, allowing it to remain competitive and fresh. Here are some of the features it boasts: Arbitrary executables: You can configure the Lambda service to run arbitrary executables to process events rather than working with language-specific functions. Custom runtimes: Users can implement their own language runtimes beyond those provided natively by Amazon. Provisioned concurrency: The ability to keep event handlers spun up and on standby to help mitigate the cold start problem of allocating resources at the time of the event. Easy access to persistence: Users can use Amazon's RDS Proxy  to connect to database instances securely from their functions and use Elastic File System to store file-based data. AWS Lambda charges based on resource usage tracked at the millisecond level. Unfortunately, the total cost of running AWS Lambda is often difficult to calculate up front because so many different factors affect the overall price.The total price is based on a number of factors: The architecture executing the functions: x86 or Arm. This is charged based on the number of requests and the duration of each request. The amount of memory allocated to the function: From 128 MB to 10,240 MB, allocated in 1 MB increments Provisioned concurrency usage: If you choose to provision concurrency to help with performance, the extra concurrency will cost more Amount of data transferred in and out of the functions Lambda@ Edge usage: If you deploy your functions closer to clients, you will be charged for that extra service. AWS Lambda is a robust, mature platform for building serverless applications. It has the benefit of experience over many other providers and still leads the way in many features and evolutions in the serverless space. Its integration with other AWS services makes it an obvious choice for those already living in Amazon's ecosystem. Unfortunately, it also inherits the cost prediction difficulties that AWS services are often criticized for.Overall, however, AWS Lambda is a strong, general choice for serverless functions. It is likely to continue its trajectory of adding features and integrations to remain competitive.