Bas Kamphuis

GM Productivity @ Magnitude. Data is Awesome. Re. my tweets / PoV's: Even a broken clock gets it right twice a day...

[Right Wing Cope @RightWingCope]

The Trump protestors in NYC are NOT having a good time 💀

[Bas Kamphuis @BasDutch1]

@JamesMaguire Great discussion, thank you for hosting James #eweekchat https://t.co/rtOgqUn2Vp

[Bas Kamphuis @BasDutch1]

@RKs2cents and hence #DataOps is the ability to overcome and increasing the value of the data that is harnessed in those legacy applications whilst creating the services that will make us successful in the future. #eweekchat https://t.co/yRSZEhnFVK

[Bas Kamphuis @BasDutch1]

@RKs2cents 100% agree - and I think it is more and more understood that the Digital transformation is not merely about launching new services but also overcoming the technical debt that keeps a team anchored in yesterdays capabilities. #eweekchat https://t.co/qm60xAmIsK

[Bas Kamphuis @BasDutch1]

@JamesMaguire A10: despite all the innovations in everything hyperscale-cloud providers do and everything startups are launching to add to the mix of capabilities, one of the hardest hurdles remains data: trying to get data out of a system an... #eweekchat https://t.co/2jZaoAswK3

[Bas Kamphuis @BasDutch1]

@JamesMaguire A10: We will continue to see a rapid pace of innovation as modern services come together / converge. And I believe it will continue to increase its importance, because digital transformations largest challenge is all about data(... #eweekchat https://t.co/y8dou0x4zk

[Bas Kamphuis @BasDutch1]

@JamesMaguire A4: Lastly the lack of intelligence within BI is a scaling challenge: there is not a whole lot of self-learning algorithms that are helping you interpret data at the BI layer of the architectural stack. #eweekchat https://t.co/Mo1G6sYMZw

[Bas Kamphuis @BasDutch1]

@JamesMaguire A4: I think there are 3 major challenges: 1: Data silos, 2: proprietary technology stacks; and 3: the state of automation. #eweekchat https://t.co/HrrFR3ierX

[Bas Kamphuis @BasDutch1]

@JamesMaguire A9: . Think about this formula for a second: (data * Model) ^ People. In other words: by making data insightful through a model (context rich and business driven preferably) many more people will be empowered to take smarter act... #eweekchat https://t.co/aYD6vEiHOK

[Bas Kamphuis @BasDutch1]

@JamesMaguire A7: probably true, probably a lot of vendors do focus here because it's such an interesting problem to solve in the bigger context of the industry challenges. We had Magnitude decide to focus and it's all about the ERP data for us. #eweekchat https://t.co/8YwN8dZ9Vg

[Bas Kamphuis @BasDutch1]

@BasDutch1 Industries like Oil and Gas, Consuoer packaged Good or Life Science wil benefit the most because the ability to react faster to a supply chain disruption is key in increasing competitiveness and achieving results #eweekchat https://t.co/1K6GgFYW2d

[Bas Kamphuis @BasDutch1]

@JamesMaguire A8 I am biased (appologies), but industries with complex supply chains and/or manufacturing operations at a global scale will reap the highest rewards. #eweekchat https://t.co/Ap28Y9Dwgu

[Bas Kamphuis @BasDutch1]

@JamesMaguire A6 but that is a key point today - Dataops is not an objective, its a core element in the ability to transform to a 'data driven organization'. Doing dataops right will help secure success, but its only one element #eweekchat https://t.co/igNQI4gWF3

[Bas Kamphuis @BasDutch1]

@JamesMaguire A6 In '21 of course the automation, or engine if you will, is provisioned as a Service in a broader analytics architecture. #eweekchat https://t.co/uC3A6gZNXE

[Bas Kamphuis @BasDutch1]

@JamesMaguire A6 within context yes on both. This is what we do at Magnitude. Specific to business apps, we are taking a lot of the proprietary IP / knowledge hurdles and enabling the customer's workforce and putting it into software code #eweekchat https://t.co/8tpDaY9l7q

[Bas Kamphuis @BasDutch1]

@samlakkundi Well said Sam #eweekchat https://t.co/AIzYXCl37n

[Bas Kamphuis @BasDutch1]

@JamesMaguire A5: It’s a combination of both: technology hasn't quite advanced to do it all, and human capital is not infinite in its capacity. And so, between those two, the challenges are probably about equal. The answer is automation. #eweekchat https://t.co/FThQLVmWit

[Bas Kamphuis @BasDutch1]

@JamesMaguire A3: And so therefore data output, data ops, in that context is a force multiplier. If I can automatically interpret, I can scale the number of insights that I can extract and the speed in which I can make these insights. #eweekchat https://t.co/fki0DxcIt3

[Bas Kamphuis @BasDutch1]

@JamesMaguire A3: The ability to make smarter decisions, to analyze better, is in a large part constrained by the amount of data scientists that you can hire, the amount of people that you can find that understand it all. #eweekchat https://t.co/jz0ggTcF7E

[Bas Kamphuis @BasDutch1]

@JamesMaguire A3: Lets go back to ‘purpose’ – our desire and ability to analyze data serves a purpose – probably something like ‘enabling better decisions that ultimately create a competitive advantage for the organization at large’. And that... #eweekchat https://t.co/l4pSiIqDih