Transcript (view)

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so we’ve Spanta quite a bit a time this morning talking about
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where data is gonna be stored how data is going to be starters are gonna be in
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Hadoop isn’t gonna be
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living and their relational repositories that you already have
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is it gonna be circulating across your organization and flat files
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and whereas how you gonna bring us all together so what we believe a class
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sorry
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is that the next big challenge in the next big thing that needs to be solved
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for
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it’s how you actually analyze data from many disparate sources and do it quickly
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so that kept me too those first topic of more data you just heard from John
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about data spewing out a lot of places it is big data there’s more data as a
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lot a variety of it
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these the state us sitting in the ER relational repositories that’s gonna
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deliver near Big Data platforms
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it’s going to continue to live and flat files
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and in addition to bat it’s gonna continue to march from a lot of external
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sources
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an external sources ranging from public sources of data
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to premium sauces update our that’s not going away and fax if anything
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there are more and more external sources coming up online
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so the big question as data consumption data now says
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how are you gonna bring together all this internal data across all these
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various repositories
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all these different data structures different data times
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and bring that together with the various a
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sources have external data as well to amplify insights
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what needs to happen is there has to be a solution and the house to real way
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to allow you to get to all the sources faster
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and actually get to enhance I trust you don’t want a fractured view
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across the various different data silos not you don’t want one solution to tap
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into
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Hadoop another solution to look into your relational repositories
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other tools to go look at your external sources
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it is important I’m gonna become more critical to get a holistic re across all
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your data sources
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that kept me to the next issue that most companies face that we work with how do
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you go
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from question to answer quickly up to this point it has been a slog to go from
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question to answer
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right you go through a process for modeling
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ATL sampling date our by the time you go through all this
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you’ve lost weeks in the process you depend on a lot of data architects along
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the way
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you depend on a lot of folks on the IT group to do it for you
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and he finally arrive at a dashboard view of your business
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and by the time you hit that inside it’s often too late
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so this whole issue of going from question to frost answer
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could not be more critical its gonna become even more important
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as data spread across many different internal repositories an external
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sources
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in addition to that as you headed inside it’s important to change the way
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that data and one actually looks at the inside
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and a way where you can now iterate on it quickly so you arrive at an inside
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and that’s not where a dance what you want to be able to do is in a raid on it
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fast
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and in the process discover more data as data generated from the SARS
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this is all about making sure that the speed of access in the speed of
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processing
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changes dramatically so you can actually get to a place where
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generative inside becomes possible and then the third aspect of it is about
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people
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up to this point we have relied again on data experts data scientists are
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specialists in the IT group
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to be the ones to bring the day together from multiple sources and deliver an
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insightful line a business
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it needs to become easier for everyone across the business to be able to see
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inside
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ads inside are made available you have to be able to get to the data quicker
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you have to be able to get to announce a quicker so that you can make a decision
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in a in a faster manner that’s important for the business and as more people come
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together
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to look at inside across disparate data sources
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what’s important is that first system makes it possible for people to
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collaborate
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across the inside wherever your located you could be sitting in different
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officers he could be distributed across the world on different teams
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but it’s critical that everyone has a way to collaborate on the inside
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and this has to be done in contact of the inside itself so that data and
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insights are not misinterpret
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so we call the state oh where collaboration and it truly is about
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bringing more people into this so they can actually collaborate in contacts on
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the inside and get to a conclusion faster
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at the end of the day this is about true democratization of data and making it
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possible for everyone
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to be able to access and view data from the many disparate sources that have a
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march and get to announce a quickly
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so with that I’m we introduce clear story here at Strada
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the team a clerestory has comes from background such as Google
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I’m clara’s today to Facebook so on so forth
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and what we’ve built is the first solution that integrates a data
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processing platform upscale
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worth a front end user application that makes it easy to access data from many
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just what sources both internal and external
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converged data on the fly through an engine
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that we call data harmonization and arrive at a visual insight very quickly
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once you arrive at a visual insight you can iterate on the fly on the inside you
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can layer data then you can remove data
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and everyone across the organization can do this
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because we made it simple and very easy and highly intuitive
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for people to actually see data across many sources and and at a rate across
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these announcers
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business users can use that data store it’s good news for
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data scientists can use that and again the goal is to make it possible for
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everyone to actually get to announce on collaborate across the answer
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where data is coming from many places so let’s take a look
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I if you haven’t had a chance to come by clerestory at I’m gonna give you a quick
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glance affair
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and you can we’ll show you more and I both later so
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as you get to a source you can arrive at an insight very quickly
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users can navigate through the and fight literally drill through visualization
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slice and dice at
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as more data is made available at the various different sources you tapping
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into
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data scored and the score is giving you
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a view into what the relevance of that data as with everything else you looking
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out
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the state is coming from various external sources an internal sources as
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well
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as you can see here and this particular example those data from
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a private source a public sources are relational repository as well as Hadoop
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all march together all done in minutes arriving at an insight on the fly
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where data is modeled on conversion on the fly you can now
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start running operations across to plan their data
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very easy it literally point-and-click everything that is shown on the screen
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is relevant to what you’re looking at so users don’t get confused and try and run
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the wrong operations on the blender data
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visualizations are generated on the fly as data is updated from the source
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as far as changing data relationships across the many sources you simply
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drag-and-drop
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you can change the view you can change the relationship see you now have a new
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view
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and as you saw out there it just a couple seconds to go from an original
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piece or something else that you needed to see
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and finally about people like I said earlier it’s about letting
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a lot of people across the organisation CBM site and collaborate on the inside
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and that such a thing here
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you can quickly invite people n people can participate in that insight
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they can be out giving you input into what for
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what you’re seeing on the screen you can add an eighth at eight straight on the
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chart
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and people construct actually collaborating in real-time
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about what they are actually looking at and context of the view and the contacts
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overstated the data
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so what’s important here is that as insights evolve because data from all
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these disparate sources are changing
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people across the organization CN updating inside
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because this is what we call a living data story as the insights in March
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people collaborate
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and they get to answers faster and everything stays in contacts
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this really is about making data Adam a
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available to everyone in the organization that is what we’ve been
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talking about
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which is dated democratization it’s more sources coming together
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coming together on the fly making it very easy for everyone to do
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and we call the state intelligence we on Rails here at strata
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and we encourage all a view to swing by before seven if you wanna see more this
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in action
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alright I’m so wet that I think I’m a little over ball turnover Telstar
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they shall