Creating an in-house data lake for business often takes millions of dollars in investment, not to mention years of work to complete. This is one of the many reasons that cloud data lakes have become so popular over the past few years. Companies today can quickly create a brand-new data lake or even migrate an existing data lake on cloud systems.
Businesses that require the agility to create these advanced systems often turn to Amazon Web Services (AWS) - one of the best-known names in cloud services today, with their data lake technologies being among the most innovative in the industry. Any business that is thinking about building a data lake in the cloud should actively consider AWS as one of their first options.
How AWS streamlines data lake setup?
Right out of the box, AWS offers businesses an exceptional environment for hosting and interacting with their data. Businesses can use the existing infrastructure to launch their data lake almost immediately by taking advantage of the following features from AWS:
Security – The security behind AWS incorporates protections at the network, software and individual file levels. Companies can be confident that every bit of data that is uploaded to an AWS data lake will be protected.
Flexibility – AWS data lakes can accept data from virtually any source - Amazon systems like Kinesis, AWS import/export Snowball, AWS Direct Connect, and more. Businesses can also direct data from the Internet of Things (IoT) devices, website traffic, in-house data collection, and much more.
Easy accessibility – Being able to access the data is perhaps the most important aspect of any data lake. AWS allows businesses to build new data applications or use one of the dozens of existing services designed to analyze and interpret the available data. Due to the growing popularity of data lakes, new tools are constantly being developed to make it easier to turn the data into useful information.
AWS AI – One of the most powerful options that can be used by businesses that have an AWS data lake is the AWS Artificial Intelligence (AI) systems, which can be used to automatically analyze data and use it to improve a wide range of services.
Creating a custom AWS data lake with Trianz
On the AWS side of things just about everything is set up and ready to go for businesses looking to create a data lake. The time-consuming portion is often in creating the interfaces between business systems and the new cloud data lake. AWS recommends working with a certified consulting partner.
Trianz is an AWS Advanced Consulting and Managed Services Partner, making us an ideal partner for building a new AWS data lake. Our consultants work closely with businesses to come up with a custom integration plan that will work seamlessly with the AWS data cloud offering features such as:
AD/ED/LDAP interfaces – Creating interfaces between active directory, enterprise directory and/or LDAP systems make it easy to manage the users and permissions for the data lake.
Data importation – Identifying all potential sources of data and determining the best importation strategy. An AWS data cloud can accept data from almost any source in its raw format, which makes importing this data much faster and easier than with most other data management systems.
User interfaces – Data is useless if users are unable to interface with it. AWS allows browser-based interfaces, command line interfaces and console interfaces. Each can be set up and configured based on individual user’s roles and responsibilities.
While setting up a new AWS data cloud, it is also important to provide training to the employees who will be interacting with the system. Our consultant will work with key members throughout the business to ensure that proper training is available and rolled out to those who will be interacting with this system. Get in touch!
