At Khano Pty Ltd we are experienced in developing data platforms on-premise and in the cloud for big Enterprises like Elisa, Banglalink, and Startups like Hepta using the right technologies for the types of data, analytical needs and business processes. We
understand the specific requirements of analytic workloads, how they differ from the operational workloads that most information systems are designed for and what are the best technologies available to store and process the data
We provide the architectural design for a data platform depending on your required use cases, leaving the design flexible enough to support changing requirements and new use cases in the future.
At Khano Pty Ltd we’ve had to deal with all kinds of data and have the experience to know when using the more complex toolset is merited and worth the extra cost in development and maintenance.
And if you really need it, we can help you make the right choices and build the system that helps you solve your problems.
We can realize a data architecture from scratch or develop additional capabilities to an existing data platform, such as data storage layer developments (data lakes and warehouses), data pipelining (ETL jobs or complex batch processing
of data) or analytical components (BI tools and AI model deployment).
Businesses often collect data in various distinct locations and technologies, such as on-premise relational databases, CRM tools, analytics tools, object storage and so on.
This may work well for operational tasks, but to develop analytics tools and AI models to generate insight from these data, it’s often necessary to integrate said data to a common platform where analytical and operational workloads can be kept separate
and the data from various sources used together.
We work with our partners to understand the nature of said data, develop an integration strategy and realize this in either a new architecture or in an existing one.
Different data and different use cases require different storage technologies. Whether it’s structured data that should be kept in a data warehouse in columnar format or unstructured data like images, video and audio, which is better kept in a data lake.
We design the appropriate storage system with fast interconnects that enable the analytics tools to access the data efficiently, providing the required performance.
Data pipelines are used for ETL jobs, and batch processing of data in analytics and machine learning workloads.
Good data pipelines are performant, robust and lend themselves well to monitoring and extending when requirements change.
The term itself is loosely defined, but quite clear from the perspective of the challenge – handling big data requires different, and far more complex, tools from small data.
At Khano Pty Ltd we’ve had to deal with all kinds of data and have the experience to know when using the more complex toolset is merited and worth the extra cost in development and maintenance.
And if you really need it, we can help you make the right choices and build the system that helps you solve your problems.
