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"Transform data into the desired custom format by taking into account semantic relationships and relying on a novel concept-oriented model of data" Way too com

by udkl 10y ago

"Transform data into the desired custom format by taking into account semantic relationships and relying on a novel concept-oriented model of data" Way too complex for an introductory line. I had to read it multiple times to get a faint idea of what you might be doing. Screenshots and illustrations might work even better. The design does not look professional. You might want to look at other SaaS sites and themes from themeforest or somewhere to get ideas on the page design. The tools is interesting. What is your target market ? Who are your users ? What are some use cases ? How do you plan on marketing the application ?

asavinov 10y ago
Thanks for your comments and suggestions. Your observations actually confirm that it is not the best idea to do everything yourself. In fact, I pivoted three times during the last several years: 1. Windows (WPF) application targeting approximately the same users as Excel, PowerBI, Tableau, Qlikview but providing self-service data wrangling functionatliy (rather than visual analytics). Problem: after finishing 90% of work I understood that I have to do the next 90% - UI development ate all my time. 2. Java framework for complex analytical data transformations targeted as the same users and tasks as, for example, Apache Spark, but providing higher performance at run time and development time (in-memory column-oriented approach). Problem: again, difficulty to attract attention which is necessary to get critical mass of users. Probably the market of classical big data technologies is too tough nowdays. 3. StreamCommandr. Same as previous but focused on in-stream analytics (instead of batch analytics) and IoT. This market seems to be empty (very rare event) and I want to provde the technology as a cloud service (PaaS), say, in IBM Bluemix, GE Predix or AWS. The users of the in-stream analytics service are supposed to be solution/application developers who want to analyze their data (e.g., from devices) in real time. So I am working on this third hypothesis by taking into account my previous mistakes and collected experience. In particular, I am going to maximally simplify everthing even if I sacrify significant pieces of functionality. Time is more important than quality.
- udkl 10y ago
  I know of a Business Analyst/manager who use databricks.com spark setup to understand/query & generate visualization from their data. I remember them saying that the various integrations to data sources that databricks provides was convenient. With Azure BI (https://powerbi.microsoft.com/en-us/ https://powerbi.microsoft.com/en-us/) & Amazon QuickSight (https://aws.amazon.com/quicksight/ https://aws.amazon.com/quicksight/) the market or such tools is getting competitive. I think your tool might be useful for small and medium businesses. I would love to chat with you just to understand what you are up to. If you want, you can contact me using the alias email from my HN profile.

by udkl 10y ago

asavinov 10y ago

Thanks for your comments and suggestions. Your observations actually confirm that it is not the best idea to do everything yourself. In fact, I pivoted three times during the last several years: 1. Windows (WPF) application targeting approximately the same users as Excel, PowerBI, Tableau, Qlikview but providing self-service data wrangling functionatliy (rather than visual analytics). Problem: after finishing 90% of work I understood that I have to do the next 90% - UI development ate all my time. 2. Java framework for complex analytical data transformations targeted as the same users and tasks as, for example, Apache Spark, but providing higher performance at run time and development time (in-memory column-oriented approach). Problem: again, difficulty to attract attention which is necessary to get critical mass of users. Probably the market of classical big data technologies is too tough nowdays. 3. StreamCommandr. Same as previous but focused on in-stream analytics (instead of batch analytics) and IoT. This market seems to be empty (very rare event) and I want to provde the technology as a cloud service (PaaS), say, in IBM Bluemix, GE Predix or AWS. The users of the in-stream analytics service are supposed to be solution/application developers who want to analyze their data (e.g., from devices) in real time. So I am working on this third hypothesis by taking into account my previous mistakes and collected experience. In particular, I am going to maximally simplify everthing even if I sacrify significant pieces of functionality. Time is more important than quality.

udkl 10y ago
I know of a Business Analyst/manager who use databricks.com spark setup to understand/query & generate visualization from their data. I remember them saying that the various integrations to data sources that databricks provides was convenient. With Azure BI (https://powerbi.microsoft.com/en-us/ https://powerbi.microsoft.com/en-us/) & Amazon QuickSight (https://aws.amazon.com/quicksight/ https://aws.amazon.com/quicksight/) the market or such tools is getting competitive. I think your tool might be useful for small and medium businesses. I would love to chat with you just to understand what you are up to. If you want, you can contact me using the alias email from my HN profile.