well, try https://www.seektable.com -- with this tool you can make a pivot table just in a few clicks and you may found it much more useful for ad-hoc reporting than Excel/Sheets. For sensitive data self-hosted version can be used.
57 karma · joined October 2, 2017
Why don't use other BI tools that could do pivot tables from Snowflake without pain? For example, our SeekTable can be used for this purpose.
We can add a connector for QuestDB if someone is really interested in this.
what BI tools currently can connect to QuestDB for ad-hoc reporting (without need to write SQL queries by hands)? I guess popular solutions like Tableau/PowerBI doesn't support QuestDB.
Is there a demand for BI tools that can use QuestDB as a data source? I'm asking about that because we can add a connector for QuestDB to our BI tool (SeekTable) with a little effort, but this has sense only if someone really will use it.
* when you make a query to this knowledge base, it has a history of your prev searches / preferences (not google)
* it can propose variants of suggestions on what is your intent in this particular query - and make much more detailed queries (auto include/exclude keywords websites etc) to multiple sources (not only google, maybe anonymously)
* it can parse results from these sources and re-arrange them (use own rank system) according to the your preferences. In this system, you can explicitly say - I hate that, and I like that, and this will affect the behavior. Yes this is 'information bubble' but it is controlled by you and not by google!
* finally, this system may work in background and handle 'research' search queries. What I mean here: currently, Google is about instant search - it gives you results in milliseconds, and that's all. It cannot spend much computations for more precise, more intellectual check of content in links from the search results - it cannot do reasoning - and you have to do that by yourself: open links from 1-st page, and close most of them immediately b/c they are not relevant for you, go to 2-nd page and so on. It would be cool if most of this could be automated - with modern natural language processing approaches and old-school prolog-like reasoning this is real and not a fantastic from sci-fi.
My vision that this kind of search assistant cannot be SaaS / closed source. It is about the freedom - and thus this should be open source / self-hosted app that can be deployed on PC or on cloud VM - but hosting should be controlled by end-users, not companies.
I don't know if something like this ever exist. If not, maybe its time to create it.
so true! Only exception is maybe CSV data.
Re SeekTable: it also supports usage scenario when data sources ('cubes') are configured by power user (with some IT background), and shares cubes/reports to others that use simple web UI to create their own reports - and this requires paid subscription for publisher only ($25/mo).
Redash can be self-hosted
(and our SeekTable also has on-premise version)
Instant results are good for sure, however very often few more seconds - in addition to instant results! - is not a problem if late, more carefully processed results can save minutes of my time - for now I spend it for opening the links and scanning the content with my eyes.
The same is about not very often but important searches that may be described as 'research about something', in this case I'm ready to make complex, well detailed query and wait even hours - then back and get well organized and intelligent results.
> Do you mean users should keep their own index of the whole web by themselves?
oh no! Users should keep only their personal data - in wide meaning, this includes all history of searches, search results, refinements, anything that ML currently uses to bring personal search experience. In addition to that, relatively small index of important content may be saved. For internet search this 'personal search' will use API of anything that can be used manually for now - google, bing, consume direct API of Twitter/FB/Medium/WolframAlpha and hundreds of connectors to other cloud services. It is important to say, that this 'delegated search calls' may be anonymized.
It will be important that search results are not limited only by what google decided to be 'top results for this user'. At this moment I can do all this manually - open N tabs, query many services, compare results, open most 'relevant' (from my human point of view, not google) links and scan them for most interesting information. I believe that all this can be automated.
> First I think you greatly overestimate how useful information about you can be. Second if that worked then it would make they problem you mentioned before (information bubble) worse...
As for now, all this just thoughts. I'm a programmer with almost 20YOE; I have understanding about how google works in general, how lucene works, how WolframAlpha works, modern approaches to NLP and search-driven queries processing, and I think - without a MVP that works, this is more belief, of course - that value of this 'personal computation engine' combined with modern ML approaches might be ultimate. Challenge, but nothing impossible!
* search engine is a cloud service, which is not controlled by user of that engine
* search gives final results in milliseconds (why? because google cannot spend many seconds/minutes for you, that's why)
* search creates information bubble (that user cannot control) because it tires to satisfy user's expectations
Most likely this new 'google-killer' will be:
* open source, because user should trust the code
* self-hosted (easily deployed in a click), not a cloud SaaS. Our search preferences have ultimate value, no one should have an access to it
* more useful than google because of accumulated data about you that are processed by computational knowledge engine (something like WolframAlpha)
* background reasoning - this engine can work continuously and utilize your own computational resources on notebook/PC and bring you brand new search insights that google never will be able to deliver (because they cannot dedicate a lot of computational resources for each google user).
Sounds good, isn't it?.. Maybe this kind of software already exists, could someone point me out?
- Google Sheets suggests pivot tables / charts that can be built on your worksheet data
- with our BI tool (https://www.seektable.com) everyone can upload even rather large (up to 500mb) CSV file, then engine suggests dimensions/measures automatically and even suggests some typical reports (suggestions are very simple as for now, just set of heuristics rules based on CSV column names). More than this, for CSV file user can 'ask' data with search-like queries and get an answer in form of pivot table.
* data sources (database tables & columns) are isolated from end users with some kind of 'model'; end-users operate in terms of this model. This model is created & maintained by 'publishers' - this is user(s) with some technical background that know database structure & SQL good enough. In large organizations this is IT specialists, in small businesses this role is covered by founders/managers with tech skills. If organization database(s) cannot handle OLAP queries directly some kind of data lake is organized to deal with slow queries.
* end users use BI tool to perform ad-hoc analysis, save & share their reports.
Also it is good idea to start from something very simple that can be configured very fast; in this way you can collect feedback from end-users (BI consumers) as early as possible, and then decide if you need to invest more in more complex / enterprise oriented BI solutions. In this context, I may recommend to check our BI tool: https://www.seektable.com (both cloud service and on-premise installations are possible).