Data operations was another opportunity for improvement, so we made sure to set strict requirements in this area. All im

The Big One is coming. To be fair, any game CD Projekt Red released after The Witcher 3 was going to be huge, but going with a cyberpunk theme made this a megaton release. Media of all forms have been obsessed with this genre for years, and fans gobble it up. It lets people like you and me glance luridly into the corners of our imagination where fears of shadowy evil governments, the horrors of technology, and the worst excesses of humanity all combine into a vile soup. Then you can turn the power off and pray that we never end up in that dystopian world. Play it or watch it, just hope we don’t live it.

At this point in time, the Data Quality initiative is moving at full steam, but there is still plenty of work to be done. We’re accelerating investments into our data foundation, designing our next generation of data engineering tools and workflows, and developing a strategy that will shift our data warehouse from a daily batch paradigm to near real-time. We are aggressively hiring data engineering leaders who will develop these architectures and drive them to completion. If you want to help us achieve these goals, check out the Airbnb Careers page.

The Data Quality initiative accomplished this revitalization through an all-in approach that addressed problems at every level. This included bringing back the Data Engineering function, setting a high technical bar for the role, and building a community for this engineering specialty. A new team was also formed to develop data engineering-specific tools. The company also developed a highly opinionated architecture and technical standards, and launched the Midas certification process to ensure all new data was built to this standard. And finally, the company up-leveled accountability by setting high expectations for data pipeline owners, specifically for operations and bug resolution.

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s of the magazine viewed my inclusion of a nonexistent son as a cardinal lapse and retracted the piece. That is their prerogative. Unfortunately, this decision has prompted widespread speculation that the article as a whole is not grounded in solid reporting, contains embellishments or is somehow fabricated or made-up.

Built with the bones of a popular and long-running tabletop RPG universe known as Shadowrun, Hong Kong is the most recent iteration of the digitized version of the franchise. This is a world where magic and technology, humans and orcs, all coexist together. Set in 2056 the titular city is now known as the Hong Kong Free Enterprise Zone and, as you probably guessed, the enterprise is anything but free and the city is run by evil corporations with aspirations of dominance. The downtrodden live in a slum of nightmarish proportions and conditions, replete with the flashing neon signs and gangland turf wars once can expect in such an Asian cinema-inspired landscape. Your character is part of a group investigating what is going on in the city and how it connects to the corporations, and the plot unfolds from there.

Last, but not least, we created new mechanisms for ensuring accountability related to data quality. We refreshed our process for reporting data quality bugs, and created a weekly Bug Review meeting for discussing high priority bugs and aligning on corrective actions. We also require that teams incorporate data pipeline SLAs into their quarterly OKR planning.

With an Orwellian-nightmare-come-true plot, the World Economic Consortium (WEC) has taken over from the world’s governments and subsumed the populace as drones for its evil machinations, rendering individual rights and freedoms a thing of the past. You play as The Silencer, formerly a member of the WEC enforcer squad who has gone over to the resistance group fighting against the bad guys, with the goal of ending their stranglehold on the little people of the world. Pretty standard stuff, but the action was quick, bloody, and well-made across both titles, and thus both games belong in your library.

In fact, this is a pattern that you’ll see often. When you need to apply a relatively simple operation on each element of an iterable object, using map() in combination with a lambda function is concise and efficient.

I’ve included these two games together because they are functionally the same, the sequel (No Regret)maintaining the same real-time action and 3/4 isometric viewpoint as the first. Hailing from the days when DOS was still the prevailing game platform, these two games were the pinnacle of cyberpunk action at the time.

Cyberpunk 2077 is a mere month away from release, so close we can almost taste it. Gamers everywhere are planning what weapons, body mods, and genitalia to give themselves. But until it drops we have to get our kicks with some classic cyberpunk gaming instead. There are dozens of these lists on the internet today, so I tried to find the road less traveled and recommend a few you may not have heard of, plus Blade Runner because everyone’s heard of Blade Runner.

This PS1 title uses a cyberpunk setting for some fun action, blasting uber-criminals in your convertible police mech through the streets of LA in 2098. Envisioning a city in flames (literally and figuratively) where criminals have the cops outgunned and out-teched, the game began life as another entry in the venerable Strike series before converting to what you see here. It controls well and is a lot of fun to play just like its brethren. With missions revolving around scenarios like “uber-criminal X turned the observatory into a plasma cannon to shoot down commercial airliners”, it’s ridiculous fun that will put you in the proper mindset for further adventures of a similar ilk.

As we set out to rebuild our data warehouse, it was clear that we needed a mechanism to ensure cohesion between data models and maintain a high quality bar across teams. We also needed a better way to surface our most trustworthy datasets to end users. To accomplish this, we launched the Midas certification process (depicted in the diagram below).

The Midas process requires stakeholders to first align on design specifications before building their pipelines. This is done via a Spec document that provides layman’s descriptions for metrics and dimensions, table schemas, pipeline diagrams, and describes non-obvious business logic and other assumptions. Once the spec is approved, a data engineer then builds the datasets and pipelines based on the agreed upon specification. The resulting data and code is then reviewed, and ultimately granted certification. The certification flags are made visible in all consumer facing data tools, and certified data is prioritized in data discoverability tools.

At this point in time, the Data Quality initiative is moving at full steam, but there is still plenty of work to be done. We’re accelerating investments into our data foundation, designing our next generation of data engineering tools and workflows, and developing a strategy that will shift our data warehouse from a daily batch paradigm to near real-time. We are aggressively hiring data engineering leaders who will develop these architectures and drive them to completion. If you want to help us achieve these goals, check out the Airbnb Careers page.

As a company matures, the requirements for its data warehouse change significantly. To meet these changing needs at Airbnb, we successfully reconstructed the data warehouse and revitalized the data engineering community. This was done as part of a company wide Data Quality initiative.