Navistar is a leading global manufacturer of commercial trucks. With a fleet of 350,000 vehicles, unscheduled maintenance and vehicle breakdowns created ongoing disruption to their business. Navistar required a diagnostics platform that would help them predict when a vehicle needed maintenance to minimize downtime.
Strong investments in an organization’s data pipeline result in greater business outcomes. Few would dispute this claim, reflected in the massive growth in the big data and analytics market which continues to fuel many organizations’ ambition to become data-driven.
“Quality is “value to some person” (quoting Jerry Weinberg) and as such is highly subjective. Because of that, there is rarely a set of metrics that can be used as a recipe for most cases; which in turn makes indicators of readiness to deploy, data to be collected, etc.
Have you ever found yourself copy-pasting the same bits of JavaScript code between different projects? Well, when this situation happens two or three times in a row, it’s usually a good indicator that you have a piece of code that is useful and reusable. So, if you are already reusing your code across several different projects, why not go the extra mile and convert it into a library that allows you to optimize this code-sharing?
Apache Hive supports transactional tables which provide ACID guarantees. There has been a significant amount of work that has gone into hive to make these transactional tables highly performant. Apache Spark provides some capabilities to access hive external tables but it cannot access hive managed tables. To access hive managed tables from spark Hive Warehouse Connector needs to be used.
