Google BigQuery is a gem because its technology is shaping the future of analytics capabilities. Talking about this Big Data jewel between women for once will not hurt (!); I spoke with Rebecca Yan Ye, Cloud Platform Partners Lead @Google Mountain View.
Here are excerpts from our discussion.
Rachel Delacour, CEO of BIME Analytics: In 2014, two trends stood out above the rest : the Cloud and Big Data, according to this very interesting Forbes article written by Joe McKendrick. He wrote that “In 2015, it’s all about the data (...) and the way to compete in today’s hyper-competitive global economy is to become a data-driven enterprise. The cloud will get us there.” What’s your point of view/experience on this?
Rebecca Ye, GCP Partners Lead : Today, “cloud” is predominantly to do things in a different place, i.e it’s about moving a virtual machine to someone else’s data center, it’s about the externalization of the existing IT infrastructure for cost savings, ease of management considerations, capex to opex model considerations, but dealing with the same primitives as on-premise architecture, such as what size of server, how much memory, how much disc space do you want, what flavor of Operating Systems. As the Big Data technologies mature, the cloud will bring developers and enterprises opportunities to do things differently, not just do it in different places but with a set of elegant APIs and great user experiences. No doubt, the explosion of data volume, variety and velocity (such as social media, Internet of Things, public data mashup) has posed a new set of new challenges, and Cloud Big Data technologies can provide the scale, reliability and performance to ingest, store and analyze data at internet scale.
RD : In this article, I also agree with this sentence “Cloud-based data analytics also relieve enterprises from the headaches involved with storage and scalability.”
As part of the BigQuery Eexecutive Tteam, could you share with us some use -cases that amazed you, that kickstarted this new era of ‘pain relief’, or that were significant for you in 2014 ? Are there any 2015 projects or enhancements to BQ that you can share with us?
RY: Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google's infrastructure. The best feature of Big Query is to find a needle in a haystack, and I’m talking about billions of rows as a haystack, and Big query will get you the answer in a matter of seconds.
For example, Big Query is used by retail companies like Rooms to go, US Cellular to measure marketing effectiveness and one of the largest insurance companies in the US is using Big Query to gain more customers insights.
We’re working hard to bring new technologies to help solve many of today’s Big Data problems. More recently, we announced the Cloud Dataflow and Pub/Sub to be added to our Big Data stack.
Google Cloud Dataflow is a simple, flexible, and yet powerful system people can use to perform data processing and orchestration tasks of any size, both batch and real time.
Google Cloud Pub/Sub is designed to provide reliable, many-to-many, asynchronous messaging between applications. Publisher applications can send messages to a “topic” and other applications can subscribe to that topic to receive the messages. By decoupling senders and receivers, Google Cloud Pub/Sub allows developers to communicate independently between written applications.
We’re also actively working with the open source community to optimize the performance and make development and deployment on Google Cloud Platform much easier.
RD: Let’s talk about our industry biggest concerns: according to Joe McKendrick (again...I found his article very relevant), “We’ve reached a point where comfort levels about putting data in the cloud are rising. Data security is always something to which enterprises need to pay a lot of attention. But it is being addressed.”
What do you think about this evolution? Have we really reached a psychological “safe” level?
RY: The Cloud Big Data adoption is a journey, some enterprises are faster than others for various reasons - for internet companies that are dealing with vast amount of users’ data, Social streaming data, or Retail companies mining Sales and Marketing data, Transportation companies meshing geo and weather data in real time - storing and analyzing the data in the cloud provides a very compelling value. For Financial Services and Healthcare industries, the regulations and “safety” concerns will probably remain for a while, but we see them beginning to move some of their data analytics functions to the cloud as well.
RD: In this article, the following sentence is for me more than just reality, it’s also a sign for “hope” : “The availability of cloud processing power and storage space also allows for inexpensive experimentation and product simulations with the data — in line with many businesses’ desires to “fail fast” their way to greater innovation. With so many emerging trends around big data and analytics, IT organizations need to create conditions that will allow analysts and data scientists to experiment.”
What I love in our current world is the amazing processing power being made available. I love the idea of having more Rosetta projects being democratized, in the same way that drones are now available for everybody. Sort of “Processing data made easy for NASA’s apprentice”. Recording more soundtracks from space, maybe having a Space Billboard Top 100 would be another crazy idea, requiring huge processing power. That would be fantastic. Having such power available - one of your Google Cloud Partners was already able to scale the Eurovision voting system - is amazing. What are the craziest projects you could think of ?
RY: I’d love to see Big Data technologies being applied in life science, and help to cure cancer. At Google X, Googlers are working on a nanopartical platform, developing a pill to detect Cancer cells. In the future, this is something completely different we can do with Big Data technologies.
RD: And in your daily life, what is your biggest Big Data footprint? Are you using devices such as Fitbit or Withings?
RY: I think my car, my LG smartwatch, smartphone are already constantly producing data and collecting data. In the future, I do see us alternating between the roles of data producers and data consumers to make our work and life more fun and effective.
RD: About “Women In Tech” : I have known the Google Cloud Platform Executive Team for a while now, and it’s the first time I am speaking to a woman. This tech world - including B2B, Cloud and Big Data - is still very “male” dominated. Are you seeing growing opportunities for women in this space? Is there a woman who has particularly influenced you as a mentor? Or as a role-model?
RY: Yes, at Google, we’re very conscious of the challenges that could rise from gender bias and we take active measures to promote diversity. My role model at Google is Jocelyn Ding, who is the VP of Operations at Google for Work. Her high integrity, passion and conviction in bringing Technology to better people’s life are very inspiring; it’s people like her at Google that makes work much more enjoyable and meaningful.
RD: Let’s end with a Geek Culture “bonus” question. When I was a kid, I was obsessed by the movie Electric Dreams, it was my first discovery of computers. Was there a movie or something in the ‘pop-culture’ that influenced you to follow this career path?
RY: I watched Matrix three times :)
RD: Thank you very much Rebecca! See you soon in San Diego for the Google Partners Teamwork 2015.
For more information about BigQuery, click on the image below. Enjoy! Rachel