I worked directly with 7 large corporations and public organizations, indirectly thru colleagues and partners many more, on analytics transformation initiatives last year. Top 3 differences vs. 2018 and earlier years (from data engineer point of view): 1/2
#InternalData + #ExternalData is a powerful combination in #Analytics. Enriching own data with external data organizations can answer broader questions about market potential, competition and industry.
@smartdatahub This is a great start, and I'm already looking forward to 10k datasets in near future, then the next major 100k milestone! No #data, no #AI 💪
Did you know human brain has a Halle Berry cell that fires when you see a picture of her? Just learned this and a few even more useful stuff about #neuroscience from @tarrysingh in #TDWIFinland event.
Immature but rapidly developing data market needs data brokers and collaboratives to combine data from public and private organizations and realize its value. Great report by @cphsolutionslab on learnings from City Data Exchange and state of data market. https://t.co/FiK1z2G1a6
Majority of a data scientist's time is spent on data preparation instead of creating value. We have fixed this by preparing data for you.
Try https://t.co/gelJ0XvugJ and start creating value.
Avoimen datan tietohakemistoihin vahvasti panostanut julkishallinto on tiedon jakamisessa yritysmailmaa edellä - spot on @MNaatula mainio kirjoitus @Tivilehti ssä metadatan hallinnasta! https://t.co/5xAag2aBVX
"Become data scientist, make money, retire early and enjoy life" @akmalchaudhri sharing serious life advice for the young generation at #BigData event by @MSFTFlux and @DataNativesConf. Wish I were 20 years younger...
Data liberation - decoupling of data from applications - transforming enterprise IT stacks, cutting integration costs. Data engineer's key takeaway from #TechArchDay event by @AccentureFI