"Star Wars: Episode VII The Last Jedi" opens in theaters today./Courtesy of Walt Disney. A film called the Empire Strikes Back set the bar for sci-fi sequels. It's still, to this day, considered by many people to be the best Star Wars film. When 2015's Force Awakens debuted to somewhat surprising critical acclaim, expectations for its sequel to follow in Empire's footsteps were unavoidable. This was the daunting task director Rian Johnson faced with The Last Jedi, the latest Star Wars installment to hit theaters.

This week, data is becoming knowledge as all streams of data are converging and leading me to the conclusion that every business is in need of the same types of data, tools, and results. From payment processing to media to rentals to retail to finance to big pharma, the same problems are coming up of "How do I ingest all kinds of data (variety), constantly changing (agile), often broken (flexible, schemaless or schema flexible), do some transformations in stream and land it in my big data environment (Hadoop with some flavors of NoSQL or data warehouse (SAP HANA or SQL Server or Oracle X) on the side)?" Oh and it's got to be fast, scalable, easy to use, and have a UI that can be used by my intern/data engineers. Some of the data is coming from IoT devices, cameras, beacons, web logs, Twitter, Facebook, 3rd party paid feeds, free feeds from NOAA, government and partner data sources, and legacy systems. So what can support text files, JSON, JMS, MQTT, REST, XML, MongoDB, S3 and a host of sources and formats?