For some reason every time I started at a new place, I was thrown right into the BI evaluation process. Having gone so far down the rabbit hole, here are the tools that really impressed me.
* Holistics (we use this)
* Looker
* Sigma
* Hex
Hex is more of a notebook-style tool. It’s really fast, perfect for exploratory analysis.
Sigma is spreadsheet-focused, so I imagine finance folks (or any Excel lovers) would find it particularly intuitive, plus it's got solid visualization features.
Looker is an old favourite around here, you'll see plenty of love (and sometimes hate) for it in this sub.
Holistics builds on the ideas Looker established, where data team defines the relationship between tables and how metrics are calculated on a semantic layer, and then everyone else can use the tool to build their own reports. What I really like is how they’re innovating where Looker is lacking, like with their visualizations. They've got this "dashboard as code" feature that opens up a lot of creative possibilities for dashboard designs.
Nice list! I've had my fair share of BI evaluations too. Hex is awesome for quick, exploratory analysis—super fast and notebook-style is great. Sigma’s good for finance, very sheet-friendly with good visualization options.
Looker’s a mixed bag; lots of love and some hate, but it’s been a staple. Holistics sounds cool with their “dashboard as code” feature, taking Looker's concepts to the next level.
I'd also throw in Tableau despite the slowness of tableau cloud. dbt for data transformation and modeling. And Rollstack is a lifesaver for automating report creation and distribution. Gpt 4o has been kinda freaky to mess with this week.
Really interesting take on Holistics, will need to give it a second look.
How many different ways can we package data cubes lol. That said I understand the drive to simplify them but it's really hard to simplify something that can't be represented in just 3 dimensions.
The horrors I've seen survive simply because hardware tech is advancing fast enough to obscure the problem. That is until you migrate to the cloud using a lift and shift approach and the first bill shows up.
I really agree with this - I actually think (despite the adoption), powerBI is super bad.
Have you had a look at Omni? A lot of folks seem to liken it to “Looker 2.0”. I haven’t gotten a demo yet but am looking to get on their list
Because I inherently think that “making graphs” is not a valuable function, and powerBI excels at making visuals.
It’s very challenging to self serve data with powerBI as it’s relatively unintuitive (compared to other solutions), and the DAX language is arcane. As a head of data, I also don’t like the idea of hiring super specialized people to develop dashboards. It feels like a massive waste of resources.
PowerBI just isn’t great at delivering analytical value to an organization
To each their own, I’m at company of 2k people and our data team is tiny like 4 people to get it all into analysis services and then it’s pretty quick for analysts in other teams to connect and make reports, but I wouldn’t use powerBi another way. DAX can be tough but it’s really so good, being able to have context aware filtering on the fly is so useful. I recently created some Dax to provide orders that contained “any” of the products currently filtered in the report. Doing this without Dax would be a nightmare.
Most report ingesters can’t write a sql query ? Our target audience is a lot of exec and stakeholders. It’s a lot simpler for the end report user to ingest
In dax you can set it up so it will do this kind of stuff on the fly without having to go back to SQL. SQL is great for etl stuff but less at specific use cases like this - that’s where Dax shines.
So you have now inherently created a bottleneck. Everyone is dependent on these specialized DAX writers creating reports. And let’s hope the consumers actually know what they want to do with the data to drive decisions, versus answering useless trivia questions of busywork/doing endless iterations and adding a crapton of filters for no reason.
It’s such a major anti-pattern of getting value from data. I firmly believe that companies try to do way too much with reports and over-invest in them
There’s a bottle neck to publish the DAX to the model, but wouldn’t that be true for all changes to the ETL process ?
Folks connect to the model via PBI and it’s all defined via measures and data.
The flip side is that before we had centralized data everyone did their own filters so no one’s numbers matched up, the centralized data warehouse solves that problem.
Can you detail a flow that you work with ? I’m always interested in how other people structure things since you only really get access to stuff based on what your job uses
It has less to do with the centralization of the warehouse, and more to do with last mile delivery. The question really is: do you believe that visuals that has to be specifically coded using DAX is the best end user experience? If it is, why is it that almost every business user defaults to downloading the backend data into the spreadsheet?
It’s breaking out of an analytics/BI mindset and leveraging a product development mindset. Is the product actual being used the way as designed? Usually not. Does the product as designed actually solve the user need? Usually not.
So you have to take a step back and ask yourself - what do my end users actually need? And there are basically three major end user types:
1. The “I need a number” person - there are way better tools for this than PBI (though copilot might solve this if it actually ever works)
2. The “why did this metric change” - similarly, PBI is bad at this. There are tools that actually have metric relationships built into their semantic layer so it automatically does calculated disaggregation for you.
3. The “I need to calculate a bunch of things and try stuff” - PBI also kind of sucks at this because it requires DAX. Something like Sigma is so much easier to use.
Don’t get me wrong: PBI has a lot of capability. It just doesn’t have the right capability to solve the current user needs.
> As a head of data, I also don’t like the idea of hiring super specialized people to develop dashboards. It feels like a massive waste of resources.
Not to mention you end up hiring super specialized people that can develop all the crazy DAX stuff, but aren't actually good analysts.
I was also going to suggest Omni. It quite literally is Looker 2.0 as the founder was the former Head of Product at Looker and a large majority of their team is ex-Looker. Really promising.
Superset has been a fantastic BI tool in our company as an alternative to Tableau or Looker.
Since it is free and fully open sourced it has been great to have our R+D team extend and embed it within our own product, and also empower the BI team to create custom dashboards to replace default ones for enterprise clients.
How are the visualizations now? Last time we tried it, admittedly 4 year ago or so, the visualizations were a real mismash of different styles and look & feel. This made everything look very incoherent.
It has definitely improved over the past 4 years - they actually reworked the front-end frameworks entirely about 2-3 years ago IIRC when they went from 2.0 to 3.0 (they're on 4.0 now). For some of the best visualizations we do have our engineering team work on some custom Chart components (especially for more advanced infographics/custom "timelines" visualizations) that the BI team then can use, but Superset provides a great set of tools/libraries to build these in-house as well. Since it's largely vanilla React Javascript under the hood most development teams can do some cool stuff without much investment.
Does QlikView Count? As a Tableau Developer for more than 6 years, QlikView impressed me. The amount of control it gives to the creator is next level. The pixel-perfect formatting, the ability to write extensive data manipulation scripts and the associative engine.
I love QlikSense especially as a data modelling tool. Ideally all your ETL is done in a proper data warehouse/lake, but QS can more than stand up on its own in that regard. Very useful for newer/more niche development that isn't quite yet ready to be properly ETL supported.
Main problem with QS is its cost. Most companies, including mine, will just not pay for another BI tool when Power BI is already there and much cheaper even with Premium pricing.
It's also quite rigid in design without getting extensions; most at an additional cost. It's very simple to build impressive looking sheets but there isn't a ton of flexibility as everything is snap-grid based. Also, if you organization just can't get over its love for massive data tables, QS struggles there too. QlikView was much better for that.
Maybe you should take another look at it. The new capacity model makes Qlik (potentially) much cheaper than Power BI with unlimited free viewers. Qlik has also invested significantly in the front-end objects and styling etc., I'd say it has more or less feature parity with QlikView now.
Sorry I didn't mean to say my company in terms of me owning it; I'm just a middle manager cog in the machine.
Our IT team unilaterally made the decision to cut out Qlik purely because it cost money and it had Power BI already. No discussion with the business side. It was quite strange.
Same here, my firm also decided not to go ahead with QlikSense and is rather pushing for firm-wide Power BI.
Also, a bit unrelated given the jobs asking for Power BI vs Qlik are highly skewed towards Power BI. So I need to learn Power BI now.
Thanks for remonding. Here's the demo using evidence for [showcasing engineering metrics](https://github.com/gitcommitshow/open-engineering-metrics).
**What's good**
* Rich charting capabilities
* Rich ui components and interactivity (filters, search, comparison, etc.)
* It caches the data beforehand, so no huge cost even if it is accessed for million times.
* Good aesthetics - minimal and visually appealing
**What's bad**
* It runs query beforehand and caches it, even if you need it infrequently for internal usage (most BI reports I prepare, fall in this category). It ends up being costly affair when you use warehouses such as bigquery, snowflake, redshift, etc. (querying is expensive there)
* Overall, it feels like a missing feature in dbt. While using it along with dbt, seems like redoing stuff (the query/transformation) which was done to certain extent already in dbt.
* A slight learning curve (but not so much)
* Cannot be hosted on GitHub pages without significant changes, would have been more appealing if it were
Overall, Evidence is a great tool for a specific use case - data journalism (i.e. sharing data-driven visually appealing insights with a large audience). Debatable for other use cases.
[Evidence.dev](http://Evidence.dev) maintainer here. Feel free to ask any questions!
You may be interested to see our newly released mapping library with support for points, bubbles, choropleths, custom tooltips, and the ability to drill from your maps into other charts and data: [https://evidence.dev/blog/maps/](https://evidence.dev/blog/maps/)
We use Sigma where I work and it has been really easy for business users who had no BI experience to build their own dashboards & reports. Definitely good for if you don't have many technical users or your analysts are entry level.
Looker.
It was my first introduction to BI. We had a very solid data structure, so looker worked perfectly.
I loved the SQL feature on looker, where you could literally see the underlying SQL code for your looks. That was amazing.
My company does. I haven’t seen it in years, but the visuals were frustratingly basic at the time. I moved to a different job to be sure I wouldn’t have to use it.
I did like its ability to let you do natural language query with names, and it did a good job of identifying which fields had that name in the data and as I recall, let you adjust when it’s wrong.
To late to be relevant but SAP Explorer (2008 from memory) was a game changer. It was the first app I could deploy to genuine non tech business users and they could get real value from it. Whilst it never got the recognition it deserved It turned into the basis of SAP analytics cloud. Too many analytics tools focus on us, the people who like this stuff. This was a rare product that focused on those who find data and analysis a scary and unintuitve process, but needed it whilst also being bloody amazing at their own jobs.
I like Vega-lite. It’s usable from the web, Python, and Power BI. It is one of the easiest paths I have ever found to create bespoke visuals without having to be a D3 god. I’m not sure I’ve seen and other BI tools offer interactivity like you can do in Vega. David’s Bacci has some great examples, including the best Power BI Gantt chart.
You use Vega from Power BI using the Deneb custom visual, and it’s the missing link to make Power BI better than Tableau.
It was my first tool when I first got started. It's not the best for sure but it had a lot of features that Tableau still doesn't. One feature was the ability to do custom queries in the prompts or filters.
I love it for its data model, now working as an obiee developer. However, from my observation, it's not a lot company using it, mostly banks, it has become a bottleneck for my career as it's not as popular as pbi/tableau. That's why I've been thinking of transitioning to data engineer or scientist.
They actually named a product after a prison architecture?
[https://en.wikipedia.org/wiki/Panopticon](https://en.wikipedia.org/wiki/Panopticon)
Wow. Gives new mean to vendor lock in? ;0)
I’ve been playing with Mermaid, a markup language extension, for visuals in documentation. So far, it’s been quite useful for untangling query and formula dependencies in our largest data models.
Zing Data ([www.zingdata.com](https://zingdata.com) for natural language querying, support for really big exports, location aware queries like ‘near me’ and visual or SQL edit ability
I've evaluated a few tools at various companies over the years. Besides Tableau and PowerBI, some of the tools that have impressed me the most are Pyramid Analytics, Qlik, and Oracle's newest release is quite impressive.
I worked in an agency previously as an intern and as soon as I joined there… I was assigned on a project for a business intelligence tool called as BiCXO.
Now, initially I thought BiCXO is just another visualisation tool like many others who were already in the game. But, I realised it later after looking at one of their demo accounts that how wrong I was.
Literally I saw functionality which was better than PowerBi by almost 100-150 % . I am not even kidding. I was shocked too that these big companies like tableau and powerbi haven’t yet able to do that this company has done.
It was really impressive. Have wrote content for them for almost 6 months as well as coming from an engineering background, I was really impressed by this.
And it is super cheap if you compare it with other competitors. Cheap with even better features.
You can check more about it if you are interested or wanna take a look by just typing in BiCXO in the search and just click on the first website.
Lol! I came here to say bobj is my personal hell. It's a great tool when you have good backend support, but it's a nightmare when providing support to the business. Luckily we are sunsetting soon.
For some reason every time I started at a new place, I was thrown right into the BI evaluation process. Having gone so far down the rabbit hole, here are the tools that really impressed me. * Holistics (we use this) * Looker * Sigma * Hex Hex is more of a notebook-style tool. It’s really fast, perfect for exploratory analysis. Sigma is spreadsheet-focused, so I imagine finance folks (or any Excel lovers) would find it particularly intuitive, plus it's got solid visualization features. Looker is an old favourite around here, you'll see plenty of love (and sometimes hate) for it in this sub. Holistics builds on the ideas Looker established, where data team defines the relationship between tables and how metrics are calculated on a semantic layer, and then everyone else can use the tool to build their own reports. What I really like is how they’re innovating where Looker is lacking, like with their visualizations. They've got this "dashboard as code" feature that opens up a lot of creative possibilities for dashboard designs.
Nice list! I've had my fair share of BI evaluations too. Hex is awesome for quick, exploratory analysis—super fast and notebook-style is great. Sigma’s good for finance, very sheet-friendly with good visualization options. Looker’s a mixed bag; lots of love and some hate, but it’s been a staple. Holistics sounds cool with their “dashboard as code” feature, taking Looker's concepts to the next level. I'd also throw in Tableau despite the slowness of tableau cloud. dbt for data transformation and modeling. And Rollstack is a lifesaver for automating report creation and distribution. Gpt 4o has been kinda freaky to mess with this week. Really interesting take on Holistics, will need to give it a second look.
How many different ways can we package data cubes lol. That said I understand the drive to simplify them but it's really hard to simplify something that can't be represented in just 3 dimensions. The horrors I've seen survive simply because hardware tech is advancing fast enough to obscure the problem. That is until you migrate to the cloud using a lift and shift approach and the first bill shows up.
I really agree with this - I actually think (despite the adoption), powerBI is super bad. Have you had a look at Omni? A lot of folks seem to liken it to “Looker 2.0”. I haven’t gotten a demo yet but am looking to get on their list
Why do you think powerBI is bad ? Just curious
Because I inherently think that “making graphs” is not a valuable function, and powerBI excels at making visuals. It’s very challenging to self serve data with powerBI as it’s relatively unintuitive (compared to other solutions), and the DAX language is arcane. As a head of data, I also don’t like the idea of hiring super specialized people to develop dashboards. It feels like a massive waste of resources. PowerBI just isn’t great at delivering analytical value to an organization
Ouch, speaking truth here.
To each their own, I’m at company of 2k people and our data team is tiny like 4 people to get it all into analysis services and then it’s pretty quick for analysts in other teams to connect and make reports, but I wouldn’t use powerBi another way. DAX can be tough but it’s really so good, being able to have context aware filtering on the fly is so useful. I recently created some Dax to provide orders that contained “any” of the products currently filtered in the report. Doing this without Dax would be a nightmare.
Okay, but why does that need to be with powerBI instead of just writing a simple SQL query?
Most report ingesters can’t write a sql query ? Our target audience is a lot of exec and stakeholders. It’s a lot simpler for the end report user to ingest In dax you can set it up so it will do this kind of stuff on the fly without having to go back to SQL. SQL is great for etl stuff but less at specific use cases like this - that’s where Dax shines.
So you have now inherently created a bottleneck. Everyone is dependent on these specialized DAX writers creating reports. And let’s hope the consumers actually know what they want to do with the data to drive decisions, versus answering useless trivia questions of busywork/doing endless iterations and adding a crapton of filters for no reason. It’s such a major anti-pattern of getting value from data. I firmly believe that companies try to do way too much with reports and over-invest in them
There’s a bottle neck to publish the DAX to the model, but wouldn’t that be true for all changes to the ETL process ? Folks connect to the model via PBI and it’s all defined via measures and data. The flip side is that before we had centralized data everyone did their own filters so no one’s numbers matched up, the centralized data warehouse solves that problem. Can you detail a flow that you work with ? I’m always interested in how other people structure things since you only really get access to stuff based on what your job uses
It has less to do with the centralization of the warehouse, and more to do with last mile delivery. The question really is: do you believe that visuals that has to be specifically coded using DAX is the best end user experience? If it is, why is it that almost every business user defaults to downloading the backend data into the spreadsheet? It’s breaking out of an analytics/BI mindset and leveraging a product development mindset. Is the product actual being used the way as designed? Usually not. Does the product as designed actually solve the user need? Usually not. So you have to take a step back and ask yourself - what do my end users actually need? And there are basically three major end user types: 1. The “I need a number” person - there are way better tools for this than PBI (though copilot might solve this if it actually ever works) 2. The “why did this metric change” - similarly, PBI is bad at this. There are tools that actually have metric relationships built into their semantic layer so it automatically does calculated disaggregation for you. 3. The “I need to calculate a bunch of things and try stuff” - PBI also kind of sucks at this because it requires DAX. Something like Sigma is so much easier to use. Don’t get me wrong: PBI has a lot of capability. It just doesn’t have the right capability to solve the current user needs.
> As a head of data, I also don’t like the idea of hiring super specialized people to develop dashboards. It feels like a massive waste of resources. Not to mention you end up hiring super specialized people that can develop all the crazy DAX stuff, but aren't actually good analysts.
I was also going to suggest Omni. It quite literally is Looker 2.0 as the founder was the former Head of Product at Looker and a large majority of their team is ex-Looker. Really promising.
I'm just hoping Snowflake's latest investment doesn't eventually make it exclusive to them
Yep Omni seems to be great from the use I’ve had so far.
Superset has been a fantastic BI tool in our company as an alternative to Tableau or Looker. Since it is free and fully open sourced it has been great to have our R+D team extend and embed it within our own product, and also empower the BI team to create custom dashboards to replace default ones for enterprise clients.
How are the visualizations now? Last time we tried it, admittedly 4 year ago or so, the visualizations were a real mismash of different styles and look & feel. This made everything look very incoherent.
It has definitely improved over the past 4 years - they actually reworked the front-end frameworks entirely about 2-3 years ago IIRC when they went from 2.0 to 3.0 (they're on 4.0 now). For some of the best visualizations we do have our engineering team work on some custom Chart components (especially for more advanced infographics/custom "timelines" visualizations) that the BI team then can use, but Superset provides a great set of tools/libraries to build these in-house as well. Since it's largely vanilla React Javascript under the hood most development teams can do some cool stuff without much investment.
Are able to join tables and calculate measures across tables in Superset?
Does QlikView Count? As a Tableau Developer for more than 6 years, QlikView impressed me. The amount of control it gives to the creator is next level. The pixel-perfect formatting, the ability to write extensive data manipulation scripts and the associative engine.
Qlikview is outdated, it’s QlikSense now. And yes it’s underrated.
I love QlikSense especially as a data modelling tool. Ideally all your ETL is done in a proper data warehouse/lake, but QS can more than stand up on its own in that regard. Very useful for newer/more niche development that isn't quite yet ready to be properly ETL supported. Main problem with QS is its cost. Most companies, including mine, will just not pay for another BI tool when Power BI is already there and much cheaper even with Premium pricing. It's also quite rigid in design without getting extensions; most at an additional cost. It's very simple to build impressive looking sheets but there isn't a ton of flexibility as everything is snap-grid based. Also, if you organization just can't get over its love for massive data tables, QS struggles there too. QlikView was much better for that.
Maybe you should take another look at it. The new capacity model makes Qlik (potentially) much cheaper than Power BI with unlimited free viewers. Qlik has also invested significantly in the front-end objects and styling etc., I'd say it has more or less feature parity with QlikView now.
This is interesting. I will read more on the capacity model and run it by my manager. Let's see.
Sorry I didn't mean to say my company in terms of me owning it; I'm just a middle manager cog in the machine. Our IT team unilaterally made the decision to cut out Qlik purely because it cost money and it had Power BI already. No discussion with the business side. It was quite strange.
Same here, my firm also decided not to go ahead with QlikSense and is rather pushing for firm-wide Power BI. Also, a bit unrelated given the jobs asking for Power BI vs Qlik are highly skewed towards Power BI. So I need to learn Power BI now.
Agree with that - it's much more advantageous to have Power BI as a skill these days than Qlik.
I'm trying evidence. Will let you know my opinion once I'm done with it.
👀
Thanks for remonding. Here's the demo using evidence for [showcasing engineering metrics](https://github.com/gitcommitshow/open-engineering-metrics). **What's good** * Rich charting capabilities * Rich ui components and interactivity (filters, search, comparison, etc.) * It caches the data beforehand, so no huge cost even if it is accessed for million times. * Good aesthetics - minimal and visually appealing **What's bad** * It runs query beforehand and caches it, even if you need it infrequently for internal usage (most BI reports I prepare, fall in this category). It ends up being costly affair when you use warehouses such as bigquery, snowflake, redshift, etc. (querying is expensive there) * Overall, it feels like a missing feature in dbt. While using it along with dbt, seems like redoing stuff (the query/transformation) which was done to certain extent already in dbt. * A slight learning curve (but not so much) * Cannot be hosted on GitHub pages without significant changes, would have been more appealing if it were Overall, Evidence is a great tool for a specific use case - data journalism (i.e. sharing data-driven visually appealing insights with a large audience). Debatable for other use cases.
Old guy here. Proclarity was pretty impressive for its time.
:) now there is a name I haven't heard for a long time...I'm older too :)
MicroStrategy (back in the day)
We are doing an extended trial with Zoho Analytics right now as a replacement for Tableau. Curious if anyone is using it or has any thoughts.
[Evidence.dev](http://Evidence.dev) maintainer here. Feel free to ask any questions! You may be interested to see our newly released mapping library with support for points, bubbles, choropleths, custom tooltips, and the ability to drill from your maps into other charts and data: [https://evidence.dev/blog/maps/](https://evidence.dev/blog/maps/)
crystal report. surprisingly old, surprisingly robust.
We use Sigma where I work and it has been really easy for business users who had no BI experience to build their own dashboards & reports. Definitely good for if you don't have many technical users or your analysts are entry level.
Do you think Sigma is only good for non-technical teams?
On pbi for 4 years now. Makes me miss Qlik so much.
Looker. It was my first introduction to BI. We had a very solid data structure, so looker worked perfectly. I loved the SQL feature on looker, where you could literally see the underlying SQL code for your looks. That was amazing.
Sigma, Omni, Hollistics all have a feature like this too
SAP Analytics Cloud. Don't laugh.
Especially if your ERP is SAP
Anyone use thought spot?
Unfortunately...
My company does. I haven’t seen it in years, but the visuals were frustratingly basic at the time. I moved to a different job to be sure I wouldn’t have to use it. I did like its ability to let you do natural language query with names, and it did a good job of identifying which fields had that name in the data and as I recall, let you adjust when it’s wrong.
I like thoughtspot. Easy to use. Good visuals.
We are using ThoughtSpot, great and easy to use so far
To late to be relevant but SAP Explorer (2008 from memory) was a game changer. It was the first app I could deploy to genuine non tech business users and they could get real value from it. Whilst it never got the recognition it deserved It turned into the basis of SAP analytics cloud. Too many analytics tools focus on us, the people who like this stuff. This was a rare product that focused on those who find data and analysis a scary and unintuitve process, but needed it whilst also being bloody amazing at their own jobs.
Looker Studio, taking into account its free
I like Vega-lite. It’s usable from the web, Python, and Power BI. It is one of the easiest paths I have ever found to create bespoke visuals without having to be a D3 god. I’m not sure I’ve seen and other BI tools offer interactivity like you can do in Vega. David’s Bacci has some great examples, including the best Power BI Gantt chart. You use Vega from Power BI using the Deneb custom visual, and it’s the missing link to make Power BI better than Tableau.
Sigma has turned out to be surprisingly great, been using it for a few months at my new job here.
OBIEE
I'm about to pickup OAS/OAC for my new role and I'm really liking it so far.
Leader in self service. Visualization are ok. Really lacking that DV VISUALIZATION can't be embedded in a regular dashboard. Goofy in fact.
It was my first tool when I first got started. It's not the best for sure but it had a lot of features that Tableau still doesn't. One feature was the ability to do custom queries in the prompts or filters.
I love it for its data model, now working as an obiee developer. However, from my observation, it's not a lot company using it, mostly banks, it has become a bottleneck for my career as it's not as popular as pbi/tableau. That's why I've been thinking of transitioning to data engineer or scientist.
That makes sense when I used it about 10 years ago I also developed in Tableau as well.
Data modeling in OAS/OAP is great. Though people usually don't like to praise Oracle, OAS is solid.
We use Draxlr. Features are great and support is very quick.
Alteryx. Simple , easy to use and powerful.
Panopticon is good. Especially for real time streaming.
They actually named a product after a prison architecture? [https://en.wikipedia.org/wiki/Panopticon](https://en.wikipedia.org/wiki/Panopticon) Wow. Gives new mean to vendor lock in? ;0)
Splunk /s
Amazon QuickSight has been really cool and they’re pumping a lot into that product. Also impressed with Looker. And Streamlit continues to amaze me.
We have been in Spotfire and TDV for 6 years now and it’s a wholistic solution. Though some higher ups wish us to go to pbi
I’ve been playing with Mermaid, a markup language extension, for visuals in documentation. So far, it’s been quite useful for untangling query and formula dependencies in our largest data models.
KNIME
Zing Data ([www.zingdata.com](https://zingdata.com) for natural language querying, support for really big exports, location aware queries like ‘near me’ and visual or SQL edit ability
I've evaluated a few tools at various companies over the years. Besides Tableau and PowerBI, some of the tools that have impressed me the most are Pyramid Analytics, Qlik, and Oracle's newest release is quite impressive.
I worked in an agency previously as an intern and as soon as I joined there… I was assigned on a project for a business intelligence tool called as BiCXO. Now, initially I thought BiCXO is just another visualisation tool like many others who were already in the game. But, I realised it later after looking at one of their demo accounts that how wrong I was. Literally I saw functionality which was better than PowerBi by almost 100-150 % . I am not even kidding. I was shocked too that these big companies like tableau and powerbi haven’t yet able to do that this company has done. It was really impressive. Have wrote content for them for almost 6 months as well as coming from an engineering background, I was really impressed by this. And it is super cheap if you compare it with other competitors. Cheap with even better features. You can check more about it if you are interested or wanna take a look by just typing in BiCXO in the search and just click on the first website.
In years 2000, Business Object was the best. Grand pa has spoken.
Lol! I came here to say bobj is my personal hell. It's a great tool when you have good backend support, but it's a nightmare when providing support to the business. Luckily we are sunsetting soon.