As volumes of big data continue to explode, data lakes are becoming essential for companies to leverage their data for competitive advantage. Research by Aberdeen shows that organizations that have deployed and are using data lakes outperform similar companies by nine percent in organic revenue growth.
Deploying data lakes, however, is often a complex challenge beyond the current IT skill sets of most companies. Because of this, many companies are now turning to “data lake as a service” to simplify, streamline and accelerate their ability to leverage data.
Data lake as a service can drive realization of benefits that longer timeline data lake deployments struggle to attain.
Data lake as a service is a business solution that enables organizations to use a data lake without having to install or maintain the technology themselves. It also makes it possible for organizations to secure the information (structured, semi-structured, or unstructured data) for their data lake on cloud infrastructure – making data easily accessible by those who need it while also protecting it from cyberattacks.
Before you decide whether to adopt this solution for your business, you should understand:
What factors to take into consideration
What options are available to you
By outsourcing the management of data lakes to an experienced managed service provider, your business can benefit from multiple features and services, such as:
Advice on Selecting a Platform - Not all cloud data lake platforms are the same, so choosing one that is the best fit for your organization is key. For example, data lake services by Trianz include full consultations on how and where your cloud data lake should be established.
Maintenance and Support - There’s no need to worry about the hardware, software, security, or compatibility with other systems. This service includes the initial setup of all these elements as well as any ongoing maintenance and support that is needed.
Limitless Capacity - When operating an on-prem data lake, you must balance your storage space with hardware availability. When using data lake as a service, however, storage capacity is always available – you only pay for what you use.
Active Backups - As with any data storage solution, an effective backup program is critical for loss avoidance. Data lake as a service includes a full backup of your data that you can rely on.
Enhanced Business Intelligence - When using data lake as a service on a cloud platform, your data is available for analytics using modern tools. The data science team at Trianz, can help you get the most out of your data by using tools such as advanced artificial intelligence (AI) and machine learning, which provide actionable reporting and other information to help drive your business forward.
Although many cloud service providers offer data lake services, we often recommend two of the biggest and most well-known: Amazon Web Services (AWS) and Microsoft Azure.
AWS - Amazon Data Lakes integrate with AWS S3 storage services on the backend, delivering high availability and reliability. Also, you get the most advanced algorithms and the most comprehensive support because more machine learning happens on AWS than any other platform in the world. In addition, AWS offers access to the most diverse analytics portfolios available, including Athena, Kinesis, DoD SRG, and PCI DSS.
Microsoft Azure - Azure offers native format storage for almost any type of document or data, minimizing the disruption of conversion. Also, by leveraging platforms like Apache Hadoop and providing native integration with Azure Active Directory, Microsoft and a managed service provider such as Trianz can make connecting data lakes to your internal systems safe and smooth. In addition, Azure offers multiple analytics tools, such as Data Lake Analytics, Machine Learning and Power BI.
Also Read: AWS Glue Databrew: A Complete Guide
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When setting up your data lake on cloud infrastructure, one of the most important things to consider is how the data will be gathered from multiple sources. The process of data integration needs to be fully planned to ensure that all relevant data is imported – and that it’s made easily accessible to those who need it.
Data integration services are a key component of an effective data lake as a service solution. Trianz advisors can help you by performing an analysis of all your current systems to ensure they can develop the right strategy for properly adding in data from every source. The exact setup varies widely from business to business. In most cases, however, the data integration requirements will have information from multiple sources, including:
Historical data from throughout the organization
Derived data generated from databases and other sources
Metadata that contains information about schema objects, applications, and other items
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Organizational data breaches can be devastating to any business. While your system is being set up and the sources of information are going through the data lake integration process, it’s crucial to look closely at your cloud security strategy and ensure that proper security is in place.
While most people think of a data breach as a system hack by an outside entity, most of these events occur internally. It could be an intentional breach by an employee, or an unintentional event where information was revealed accidentally. Therefore, security starts with creating and managing the right access permissions.
As part of data lake as a service, each employee’s level of access is carefully determined based on their role and what business need they have for the system. Once the permissions are in place, employees will be able to access the information they need from anywhere, thanks to the data lake on the cloud.
Data lake as a service can turn a potentially time-consuming, costly, and complicated data lake deployment into a much easier, faster, and cost-effective effort. With the support of a data lake as a service provider, your organization can more quickly realize multiple benefits – such as real-time, accessible data that can be turned into valuable insights that drive informed decision making.
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