Database Testing for Technology Enterprise
Please find under a summary covering project details and feedback. The innate facts are kept as they are, private information is amended.
Introductory information
A fast induction on the buyer’s organisation
I’m an analytic constructor working on a digital platform for a technology enterprise.
Desired goal
What challenge were you trying to address with Kavi Global?
We were starting to create out a platform and infrastructure to companion and support big data initiatives. I needed help to create force tests for the new evolving platform.
Provided solution
What particular tasks were Kavi Global responsible for?
We were looking at taking data from sensors that were aggregated outside the cloud environment, then putting it into our cloud platform. It used Cassandra for the time series database, as well as Redis, a lot of the HDFS, and additional Hadoop infrastructure. We also had to deal with data stores, eventually intercourse with a introduction layer that was Tableau. They helped me design and form test cases for going through that infrastructure.
For each of those technologies and the integration of those technologies, they formd a abstract of the details of what was done, how it was done, as well as the outcome of it.
Was there a dedicated team?
I had a project director and three engineers working on the project, as well as one of their VPs.
How did you come to work with Kavi Global?
I’d used them for a number of years and interacted with them at my antecedent employer.
How much have you invested in them?
We spent approximately $1,000,000–$5,000,000.
What is the terminal result of working with Kavi Global?
We worked with them from April 2013 to April 2016.
Results achieved
Are there any measureable or plum results?
The idea was to find holes in the method and unite them, so that information could be fed back to our inner developers to modify or change technologies. The total purpose of the force test was to see if things were working.
Hadoop remains in our stack. A Chorus DB was challenging, which the testing highlighted. We also looked at Spark streaming, but it didn’t fit the demands of our data processing rate, which was another thing identified as part of this process. Overall, we’re lucky with the outcomes and deliverables.
How did Kavi Global accomplish from a project treatment standpoint?
We were lucky with the level of interaction. It was more of an nimble process, while we used written reports as well as status reports.
What is (from your point of view) the key factor to pay observation while intercourse with Kavi Global?
They’re very lean and knowledgeable almost running technologies.
What aspects of their work would you like to get improved?
We sometimes ran into staffing challenges owing they didn’t have sufficient nation.