Data Podcast Rajib Bahar, Shabnam Khan

Joe Sack is a Principal Program Manager in the Azure SQL Database and SQL Server product team at Microsoft, with a focus on the Query Processor. Joe is an author and speaker with over 20 years of experience in the industry, specializing in performance tuning, high availability and disaster recovery.

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:

RB - Your team created Adaptive Query Processing or QP. It is new in SQL Server 2017 and SQL Azure. As we know, SQL Server uses query plan internally to run tsql statements. Sometimes the plan chosen by the query optimizer is not optimal for reasons such as incorrect cardinal estimate and various other issues. What are some other pain points Adaptive QP is meant to cure?

SB - Adapative QP's strength lies behind Batch mode memory grant feedback, Batch mode adaptive joins, Interleaved execution... How do they work internally?

RB - What are steps to enabling QP and some best practices? Can you tell us what's in the pipe line for upcoming enhancement?

SB - How do we connect with you on Social Media?

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Bill Inmon – the “father of data warehouse” – has written 57 books published in nine languages. Bill’s latest adventure is the building of technology known as textual disambiguation – technology that reads raw text in a narrative format and allows the text to be placed in a conventional data base so that it can be analyzed by standard analytical technology, thereby creating unique business value for Big Data/unstructured data. Bill was named by ComputerWorld as one of the ten most influential people in the history of the computer profession. Bill lives in Castle Rock, Colorado. For more information about textual disambiguation refer to www.forestrimtech.com.

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:

SB - In the 1970s, you have coined the term, "Datawarehouse". There are countless Data gurus referring to you as the father of "Datawarehousing". We are curious how did your journey start? What did you envision a "Datawarehouse" to be back then, and now?

RB - Who were the earliest adopter? What were some interesting discoveries back then? How has the industry evolved?

SB - In current state of the Data industry, do you think Datawarehousing is relevant in this hyped up age of Big Data and Data Science? Do these technologies simply compliment existing Data practices? What is your thought on it?

RB- One of your project in the data space is called Textual ETL... What is it about? Is it a theoretical concept? Are there any tool in the industry that meets the standard?

SB - Your recent publications are on Taxonomies, and Textual Analytics... Our knowledge on it is quite limited. Please enlighten us about the use case scenario for which it's relevant.

RB - How do we connect with you in Social media such as Twitter or Blog?

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Varun Bhartia is the cofounder of BeeHyve.io an online learning platform for computer science students around the world - helping students connect with each other and with the best career opportunities. He has spend his entire career working in technology NASA, Microsoft, Facebook, and Uber. He has an undergraduate degree from the university of arizona and an mba from Harvard.

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:

RB - You have served some of the most interesting and awesome organizations... As a product manager, what is the most valuable lesson you have learned?

SB - Recently, you left Uber to launch a startup venture called Beehyve so that college students can utilize it as a portal to find exams and homework from prior years... I can see why students would love it... If they can predict the questions on the next test, it'll definitely add value in their academic career. On the other hand, Don't you think professor would hate this idea if they had to do additional homework on coming up with unique test each year? Won't that add risk to your venture? How did you go about critically analyzing all the risk and benefits? What's your vision behind it?

RB - I understand you are working on a Data Vertical. How do you plan to achieve it? Is Cloud computing or Big Data involved in any way?

SB - Lately, IoT is getting similar kind of positive attention Data Science, Cloud Computing, and Big Data part of the world are receiving? Weren't you involved in an IoT competition in Minnesota? Can you tell us your thoughts on it?

RB - How do we connect with you in Twitter, LinkedIn or Blog?

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Michael Ludwig is a Data Solution Architect at Microsoft, where he works on Machine Learning, Big Data and Blockchain applications on the Azure platform. Prior to joining Microsoft, Michael worked at Silver Bay, designing and optimizing geographical and financial statistical analysis solutions (mostly regression analysis and clustering). Before that, he was a database architect and then the lead systems architect of a multi-tenant cloud-based Internet-of-Things application for LogicPD, in Minneapolis.

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:
RB - What is the purpose of a graph database? Why do we use it?

SB - Does GoogleMap use graph databases in it's application?

RB - What are the major Graph Systems out there? How does Apache Gremlin fit into that?

SB - SQL Server 2017 has support for graph table.How do you implement it?

RB - How is this similar or dis-similar to graph computing solution implemented in vendor agnostic tools such as Apache Tinker pop?

SB- Who can be involved in coding community of TinkerPop?

RB - How do we connect with you professionally?

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Frank La Vigne leads the Data & Analytics practice at Wintellect and co-hosts the DataDriven podcast. He blogs regularly at FranksWorld.com and you can watch him on his YouTube channel, “Frank’s World TV” (FranksWorld.TV).

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:

RB - You have recently gone through Microsoft's Professional Certification for Data Scientists. Also, you are training others in this area. What are the 4 units of this Data Science certification program, and where does the units of modules also overlap with Microsoft's Big Data certifiation program?

SB - Can you tell us a little bit about the Cortana Intelligence Capstone project in Data Science certification? What sort of time committment and technical knowledge required?

RB - We often see questionable studies stating something like coffee is unhealthy followed by a counter study contradicting it? Does statistics or overfitting a data model play a role in it?

SB - One of the cool thing you do is co-hosting the "Data Driven" podcast with Andy Leonard. He was our guest in the past. In your facebook page for "Data Driven" podcast, your listeners also get to become your viewer and see live videos from Data Science, SQL Server, & other Technology related conferences. What are some insights from recent big conferences.

RB - How do we connect with you in Twitter or Blogs or Social Media in general?

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Curtis Seare is a co-host of the Data Crunch podcast, a Tableau and Trifacta instructor, and the Director of Analytics at Shelfbucks, a retail analytics startup in Austin, Texas. He’s worked for almost a decade in the data-science field across multiple companies and industries. He’s solved problems spanning IoT, retail, marketing, sales, competitive intelligence, nonprofit donations, and product development, among others. Bringing organizational change and innovation in analytical processes has been the center of his work.

Interviewer: Rajib Bahar, Shabnam Khan

Agenda:

RB - Please give us a little background on Data Crunch podcast's history.

SB - We have listened to your Data Crunch episodes highlighting some really interesting applications of analytics such as preventing honey bee fallout, eradicating malaria in Zambia etc. Please enlighten us more on what you have discovered in your research.

RB - What are some top application of IoT that retailers find useful?

SB - One of the buzzword associated with IoT is streaming analytics. How is this different from standard analytics that we know or understand?

RB - In our lifetime, we may find ourselves in a situation where we over-analyze a problem leading to analysis-paralysis. Is there a methodology do you follow in keeping solutions simple with complex analytics project.

SB - How do we connect with you on Twitter or Social Media or blog?

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