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[Datopian / Viderum pitch] People have X problems and Y use cases and we…
[Datopian / Viderum pitch] People have X problems and Y use cases and we offer a solution to this in the form of an open-source (and therefore flexible?) easy to customize full-stack data management solution together with professional implementation services; we are targetting these markets (this need for this customer, this need for that customer etc) and our competitive advantage is X, Y, Z; we are building on our existing assets A, B, C and our technical roadmap involves this specific work
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Current solutions are X, Y, Z
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Our solution provides is A, B, C and provides X, Y, Z
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These are key trends ...
DATA for the MASSES. DATA IS PART OF DOING BUSINESS. LESS PROFESSIONAL / DEMOCRATISATION of DATA USE GROWTH in DEMAND and AVAILABILITY re DATA** [esp non-expert - "down the curve"] Huge expansion in set of people creating, curating, publishing and consuming data. Naturally people are less sophisticated etc. Data warehouse to the spreadsheet data lake ...
Many more people working with data [working = curation, analysis, ... ]
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SMALL PIECES LOOSELY JOINED / NOT ONE PLATFORM TO RULE THEM ALL People who are publishing data need to describe their data in platform agnostic ways ... [the reality don't work on a centralized platform - they use many different tools e.g. excel, tableau, pandas etc etc]
End users e.g. analysts (people who turn data into insight) or app developers (but not data engineers)
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DATA PROCESSING CHAIN: creation, curation (ready to analyse), [publication], consumption (analysis, data-driven app to produces insight). It turns out that most of the work is in getting data ready for analysis (although the focus, visibility and value is in the analysis e.g. the viz) even assuming data available. e.g. 80/20 easily (80% in wrangling)
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This implies ...
Data provenance is more important as much more data out there with more insight being based on it plus political climate etc [authority and trust of the claims made on the basis of this data]
Even putting aside end users there is a rich need for tools for administration and curation of data [the publication chain] (is there personal data in there? how do you mix in other datasets, is the data contextually] pre-publication users - HUGE untapped potential
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Need tools that can integrate across different systems and data structures etc. Frameworks more than platforms ...
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Data publication is a thing ... [preparing, curating etc is a defined activity]
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