MORE, HEAD OVER TO REINFORCE LEARNING.
PREVIOUSLY KNOWN AS AZURE SQL DATA
SET-UP IN THE WORLD. >> GOOD MORNING.
ARE. I JUST WANT TO SAY SUPER THANKS
OF PEOPLE FROM AROUND THE WORLD
AT STRANGE TIME, INCLUDING OUR VERY
FOR SPEAKING TO US FROM YOUR TIME
DIVE IN. TALK TO ME MORE ABOUT WHAT
QUESTION BECAUSE, HONESTLY, I LOVE
I FOCUS ON. NUMBER ONE, WITH SYNAPSE,
WEAR MANY HATS AT SYNAPSE. I WAS
PRODUCT, A LOT OF INTEGRATION, MANY
BUILD SOME OF THE CORE PLATFORM
INTERACTIONS SEAMLESS. SUPER PROUD
THE PROJECT MANAGERS AT MICROSOFT,
FEEDBACK. I LOVE LOOKING AT THE
CUSTOMERS FROM COMMUNITY, WHAT THE
THOSE AND LACK AT THOSE RESULTS
THAT WAY. IT'S ALL PRODUCT MANAGERS
THE THING I'M MOST PROUD OF, HONESTLY,
ME. THIS IS A CASE OF IT TAKES A
USER EXPERIENCE TEAM. I'M TALKING
MANAGERS. WE HAVE A GREAT SET OF
VERY DEDICATED, WE LEARN FROM EACH
A GREAT CULTURE. I TRULY BELIEVE
THE OUTCOMES FROM THE CUSTOMERS
AGREE. IT SOUNDS LIKE A VERY EXCITING
A GOOD SHOUT-OUT FOR YOUR TEAM THERE.
MIGHT HAVE LOTS OF EXPERTS WATCHING
SOME BEGINNERS. CAN YOU KIND OF
ANALYTICS? >> ABSOLUTELY. SO YOU
THIS INTO AZURE SYNAPSE ANALYTICS.
BRINGS TOGETHER DATA WAREHOUSE ANALYZING
CUSTOMERS ARE HAVING TODAY WHEN
SYSTEM TO DRIVE INSIGHT TO THEIR
MULTIPLE TECHNOLOGIES, SERVICES,
THE EXPERTISE AND TIME TO WIRE THESE
SYNAPSE ANALYTICS IS TRYING TO ANSWER
IN AZURE? THE ANSWER IS SYNAPSE.
I BELIEVE IN THE POWER OF ONE. IT'S
THAT WORKS WITH ANY DATA ANYWHERE
LOVES USES THE PHRASE IT'S NOT ONE
THAT. IT'S ONE PRODUCT THAT WORKS
FOUR KEY CAPABILITIES IN SYNAPSE:
SQL TECHNOLOGY EVERYONE IS FAMILIAR
WITH SPARK. IT'S PIPELINE, ALL ABOUT
AND FINALLY STUDIO, OUR UNIFIED
FOUR PIECES MAKE UP AZURE SYNAPSE
WAS JUST IN THE REALM OF DATA WAREHOUSE
THEM TOGETHER IN A NEW UNIFIED PRODUCT.
DON'T KNOW WHERE TO START. FIRST,
IN 2019. MY CO-HOST SAID ROHAN DID
HE WAS IN THE MIDDLE OF THE EXPO
WHAT IS THIS ALL ABOUT? TELL US
>> WELL, WE DID TWO THINGS. WE REVEALED
THAT'S AN EXISTING GH SERVICE. WHAT
FUTURE. THAT TAKES THE FORM OF SOMETHING
A THING I MENTIONED EARLIER THAT
PIPELINE, AND STUDIO. NOW, THE REVIEW
OF EXCITEMENT. THE FEEDBACK, UNIVERSALLY,
VISION, THEY FELT LIKE IT COULD
QUESTION: WHEN CAN I GET IT. WHAT
WITH OVER 100 CUSTOMERS USING SYNAPSE
BEEN DOING DURING THAT TIME IS LEARNING
FEEDBACK HAS BEEN AROUND SECURITY,
MODEL, AND SEAMLESSNESS. HOW DO
HOW WE LEAD UP TO BUILD 2020. >>
LEARN ABOUT OPERATIONS TO SCALE
WANT FROM IT, I GUESS, AS WELL,
FEEDBACK. SO NOW WE ARE IN MAY 2020.
SAW A MENTION IN THE KEYNOTE, BUT
>> WELL, THE FIRST AND MOST IMPORTANT
PREVIEW. NOW WE'RE IN JUST PREVIEW.
SYNAPSE. YOU WILL SEE THE FOLLOWING
JUST A FEW QUESTIONS. PICK A STORAGE
YOU CAN BEGIN USING SQL ANALYTIC,
TO REALLY START DOING YOUR INSIGHTS.
I SAW THE LIST OF ALL THE THINGS
I WILL FOCUS ON KEY ONES TO LAND
IT EASY TO SHARE DATA BETWEEN THE
THE UNIFIED METADATA SYSTEM. WE'VE
AND BRINGING IT UP TO THE SAME BAR.
NOW WE HAVE A ROLE-BASED SECURITY
BI INTEGRATION. AND ONE OF THE MOST
TALK ABOUT ANY DATA AT ANY SCALE,
BROADENS THAT. NOW, IN ADDITION
DATA THAT'S IN STORAGE ACCOUNTS
ABOUT DATA THAT'S IN COSMOS DB.
THE ANALYTICS ANSWER FOR ANYTHING
CONTINUED REFINEMENT ABOUT EVERY
IT SEAMLESS. >> FANTASTIC. I WAS
THE KEYNOTE, I WAS AGGRESSIVELY
I HAD TO ASK YOU ABOUT IT. THANK
EXCITING TO SEE. THERE'S IMPROVEMENTS
IT'S THE POWER BI OR THE END ALMOST
YOUR DATA BETTER, THE COLLABORATION
IS IT A CHOICE. IT'S ABOUT BRINGING
OF THE THINGS I WOULD LOVE TO DO,
DEMOS FOR US? CAN YOU SHOW US AZURE
WE HAVE, I HAVE TO TELL YOU IT'S
>> THAT'S COOL. >> THE TIP OF THE
LET'S START WITH WHAT I'M LOOKING
OUR WEB NATIVE EXPERIENCE THAT BRINGS
HAS SIX WHAT WE CALL ACTIVITY HUBS.
TO CENTER YOUR ACTIVITY ON CERTAIN
HUB. THE PURPOSE OF THE HOME HUB
OF AN ANALYTICS SOLUTION. WE'VE
DATA, WHERE IT IS, ANALYZE THE DATA
BI. IN THE DEMO, I'M GOING TO FOCUS
THAT'S WHERE YOU'RE GOING TO SEE
TOGETHER IN THIS UNIFIED VISION
TO SEE WHERE WE HAVE MADE THINGS
FIRST HUB, WHICH IS CALLED DATA.
DATA. WE HAVE, LIKE, 90 CONNECTORS,
AS WELL AS CLOUD SOURCES. WE LAND
THEM IN MY ACCOUNT. IT'S THE FAMOUS
EXPORTED IT IN TWO VERY COMMON FORMATS.
WHICH IS POPULAR IN THE SPARK WORLD.
WITH NOTEBOOK, THAT'S WHERE SPARK
A NOTEBOOK I BUILT. YOU WILL GET
HAS TWO CELLS IN IT. THE FIRST CELL
SPACE HERE. IT'S ESSENTIALLY A SINGLE
WITH SPARK A PARKAY FILE. THIS READS
ARE ONE-LINERS. WHAT YOU SHOULD
TO WRITE ABOUT SECURITY. I DIDN'T
AUTHENTICATION WORKED BECAUSE OF
IN BOTH OF THESE CASES, I DIDN'T
CASE, IT'S IN THE FILE. DATA ABILITY
THE EXPLORATION PHASE OF USING DATA.
SPARK. WE'VE MADE IT SEAMLESS IN
SQL WORLD BECAUSE IN THE SQL WORLD,
VERY DIFFERENT. I'M GOING TO OPEN
NOW, WHAT YOU MIGHT HAVE DONE IN
CREATE AN EXTERNAL TABLE IN A DATA
ALL OF THESE OBJECTS JUST TO READ
LOOK AT THE FIRST LINE. SELECT TOP
FILE NAME, THE PARCAY FILE. IT HAS
SPARK WORLD. IT'S ONE-LINER. AUTHENTICATION
COURSE, THIS JUST MAKES IT SUPER,
TO DO ANY SCHEMA INFERENCE. IT DOES
CAN CREATE SEPARATE TABLES AND SPECIFY
IN SEEING THE DATA YOU HAVE, IMAGINING
NOW, LET'S TAKE A LOOK AT DATA THAT
THE LAKE. LET'S TAKE A LOOK AT TABLES.
JUST GOING TO EXPAND THAT OUT IN
I SEE UNDER WORK SPACE SEVERAL DATABASES.
SQL DV1 AND ANOTHER DATABASE, A
NYC TAXI. I'M GOING TO FOCUS ON
THESE TWO SYSTEMS. TRADITIONALLY,
LET'S TAKE A LOOK AT WHAT IT LOOKS
IN THIS NOTEBOOK. THERE'S ONLY FOUR
JUST TALK ABOUT WHAT THOSE LINES
THE SQL SPARK CONNECTOR. FIRST LINE,
TABLE. WHAT COULD BE SIMPLER? NEXT
PRETTY OBVIOUS. NEXT LINE, TAKE
TO AGGREGATES. AND THEN PREPARE
LINES THAT WOULD TAKE YOU A LOT
WE HAVE FULL SUPPORT IN SQL SPARK.
WE'RE OUT OF TIME. IT'S AMAZING
EVERYONE UP IN THE AUDIENCE TO GO
WANT TO LEARN MORE ABOUT WHAT'S
MS/SIGNOUT. THANK YOU FOR WAKING
>> NOW, LET'S HEAR MORE ABOUT MASTERFUL
BLACK BELT IN . >> IN MY BUSINESS
AZURE. IN MY PRIVATE LIFE -- IT'S
PROGRAMMING CLUBS FOR KIDS BETWEEN
HOMETOWN LIN KS IN AUSTRIA 5 YEARS
FRIDAY AFTERNOON. AND THERE WE USE
WEBSITES WITH YOUNG CODERS AND SET
THE CLOUD AND AWESOME WORLD. AND
VIRTUAL TINKERING COURSES. AND MOVING
WELL. AND KIDS ARE COMING AND GIVING
ACR OSS AUSTRIA STRONGER IN ONL
THAT'S SUCH A GOOD ONE TO WATCH.
WISH THAT I HAD A BIT OF THAT IN
AI MACHINE LEARNING ARE TRANSFORMIN
WE'RE MORE DEPENDENT ON THE CUTTING
TO YOU TO BUILD POSITIVE OUTCOMES
TO LEA RN ABOUT THIS RESPONSIBLE
AND THANK YOU ALL FOR JOINING. ON
YOU FOR HAVING US. >> OF COURSE,
YOU BECAUSE I HAVE -- IF I WAS INTRODUCING
PEOPLE IS AMAZING AND THAT'S ALL
LIKE YOU TO DO IS EACH INTRODUCE
TO GO FIRST. >> SURE, I'M WILLEM
I TYPICALLY HELP CUSTOMERS GET STARTED
DATA PLATFORMS. AND IN THE SPARE
ACROSS THE WORLD DOING ALL SORTS
TO TO TEACH EACH OTHER ABOUT MACHINE
GENERALLY CODING, THAT'S WHAT I
YOU INTRODUCE YOURSELF? >> YEAH,
WALLIC, A SENIOR PRINCIPAL WOR KER
RESEARCHER W BY TRAINING. WAY BEFORE
WORK IS ON FAIRNE FAIRNESS AND INT
GROUP ON FAIRNESS, AND ALSO A CONTRIBUT
WAS RELEASED THI S WEEK. >> FANTASTIC
FIRST MEHRNOOSH CAN YOU INTRODUCE
SAMEKI FROM BOSTON AND I'M A SENIOR
EFFORTS BEHIND TWO OF THE OPEN SOU
ML AND FREE LEARN. >> FANTASTIC,
COMMUNITY HERO IN WILLEM. AND HANNA
SPEAKS WITH ETHICS AND AI. AND MEHRNOOSH
SO I JUST WANT TO THANK EVERYONE
MORE TIME THAN NORMAL TO QUIZ YOU
RESPONSIBLE ML . SO I WOULD LOVE
ABOUT SOME OF THE ANNOUNCEMENT AT
MORE ABOUT RESPONSIBLE ML AND WHAT
LEARNING TEAM. >> ABSOLUTELY, AS
IN THE CONFERENCE THAT IS PRETTY
OF THEM HELPING YOU UNDERSTAND THE
MAKE AIZ ATION. . WHAT FACTORS WENT
OVERALL HOW THE MODEL IS MAKING
LEVEL. AND WE HAVE A FAIRNESS ASSESSME
KIT THAT IS CALLED FREE LEARN BASED
AND HER TEAM, AND BASICALLY THA
FACT THAT WE UNDERSTAND THAT AI
THERE ARE MULTIPLE TYPES OF HARMS
HELPS YOU UND ERSTAN D THE UNFAIRNESS
TO MITIGATE THE UNFAIRNESS. WE WER
AND DEPLOY RESPONSIBIL ITY THE ARTIFICIAL
ONE BLOCKER FOR A LOT OF EXECUTIVES
LEARNING DEVELOPERS TO REALLY GET
RELEASING IN THE OPEN SO EVERYONE
THE EFFORT TO CODEVELOP WITH US.
LEARNING BECAUSE WE ONLY WANT THE
ACCESS TO THE STATE OF THE ART SET
CONTROL AND A LOT OF UNDERSTANDING
LEARNING LIFECYCLE. >> I WAS GOING
LEARNING AND IN THE SDK AND I JUST
MOMENT TO GO IN THERE AND TAKE A
FIRST THING I'LL BE DOING. INTERESTING
AND THEN STRAIGHT INTO THE PRODUCTS.
SO LOVE IT'S IN THERE. AND I GUESS
HANNA, YOU MENTIONED YOU HAVE BEEN
FRAMEWORK. AND YOU ALSO HAVE A MUCH
BASE, CAN YOU TELL US A LITTLE BIT
AND ASSUMING IT'S NOT A ONE AND
>> ABSOLUTELY, I WOULD LOVE TO TALK
THE LAST FEW YEARS IS THE GROWING
DISADVANTAGE ALR EADY DISADVAN TAGED
THE ISSUES WE HAVE TO ADDRESS NOT
A BRO ADER SOCIAL PERSPECTIVE. THE
OF THE DATA ORIZ DA D D D D D DATA
INTERACT IN THE REAL WORLD WITH
LIVES IMPACTED BY THEM WE START
WE'RE DEALING WITH THE TOPIC THAT
INC REDIBLY USEFUL FOR UNDERSTANDING
WITH MACHINE LEARNING. WITH ALLOCATION
AROUND QUALITY OF SERVICE, SO DOES
AS WELL FOR ONE GROUP AS IT DOES
DIGGING INTO THESE KIND OF ISSUES
AND MAYBE DIFFERENT WAYS WE WANT
AND DEPLOYMEN T WE HAVE TO USE OTHER
ONE THINGS FOR EXAMPLE MY TEAM HAS
CHECKLIST, AND I DON'T MEAN T O
CHECKLIST AND IT'S DONE. MANY OF
FOR CONVERSATION AND DISCUSSION
WITH THE SPACE EVEN THOUGH IT'S
LAM OF THI NGS TECHNOLOGISTS USUALLY
LEARN AND BROADER EDUCATION IN THE
THESE KIND OF ISSUES FROM DAY ONE
FIRST STEP TO MAKING PROGRESS. ANOTHER
THINKING ABOUT ISSUES LIKE FAIRNESS,
AWAY FROM THE TRADITIONAL TECH FIRST,
OF THAT KIND OF STUFF MENTALITY
Y. AND SO IF I DO THIS WHAT WILL
LIVESES AND SOCIETY AS A WHOLE?
CULTURE CHANGE YOU NEED A WIDE VAR
MATERIALSES AND SO ON AND SO FORTH.
BEEN DOING WORK IN THIS FOR QUITE
TO HEAR THE COLLABORATION INTO ENGINEERING
ALL ON THIS LEARNING JOURNEY, RIGHT?
AS THOSE BUILDING MODELS TO HOP
THIS IS GOING TO BE DESIGNED IN
WE SAY ABOUT SECURITY . >> EXACTLY,
FAIRNESS IS NOT SOMETHING THAT CAN
SOMETHING THAT HAS TO BE THOUGHT
SITING TO MICROSOFT COMMITTING TO
THIS. ONE OF OF THE ULTIMATE GOALS
WE HAV E ASS ESSMENT DASHBOARD COMPONENT
EXPAND TO OTHER RESOURCES AS WELL.
WANT PARTICULAR FAI RNESS METRICS
AND SEE THI S EXPAND TO OTHER MATERIALS
THE ALLOCATION ISSUES. SO HERE FOR
IN MOVING TO STEREOTYPING AND DEN
THE Y'RE MUCH MORE SOCIALI O TECHNICAL
ON THEM FROM A TECHNICAL PERSPECTIVE.
BROADER SPACE AND HELP DEVELOPERS
EXCITING TO HEAR THE COMING OF RESEARCH
EXCITING TO SEE THINGS HAPPEN IN
MAKE IT OUT TO THE TOOLS AND RESOURCES
>> I WAS GOING TO SAY IT FEELS WE'RE
3 TIMES TODAY WE SPOKE TO PEOPLE
THEY'RE SO CLOSELY COLLABORATED
IT IS. SO IT'S FASCINATING TO SEE
ELY WE'RE LIKE WHERE CAN IT BE USED.
JUST WRITING ANOTHER ACADEMIC PAPER.
IN THE WORLD AND PEOPLE ENGAGING
IT MAKE A DIFFERENCE. >> -- DON'T
THANK YOU SO MUCH HANNA, FOR THE
THE CONVERSA TION A LITTLE BIT TO
AI COMMUNITY. AND SO WILLEM LEADS
WHO DON'T KNOW. GO THERE AND IF
IS THE COMMUNITY TO BE A PART OF.
CLOSE WITH WILLEM AND HIS TEAM,
A CHANCE JUST BEFORE BUILD TO HAVE
MEHRNOOS H AND HANNA ARE TALKING
WHAT YOU FOUND. >> YEAH, I GOT A
WEEKS BEFORE BUILD. BACK THEN NOT
THE PAP ERS THAT HANNA AND MEHRNOOSH
TO DO. AND ESPECIALLY IN THE FIELD
READ TH OSE PAPERS THEY GAVE VALUABLE
FAI R LEARN IT'S THE SAME. I TRIED
MOLD EHE MODELS WAS UNFAIR TO FEM