GoodData vs. WPS Analytics

GoodData is well suited when you have a lot of data sources and you need a single location where you can pipe the data into and then create insights/charts/analytics based on the data you've piped in there. It's also great if you want to customize how the datasets interact with each other and what that logical data model looks like. Super super intuitive there. I think it's not great for data presentation if your product is presenting data to your customers. For internal use, it's great

Incentivized

WPS Analytics allowed our company's business users to keep using their existing programs while getting similar results with much less learning time. It's a great accomplishment when software for business users is changed—excellent relationships with providers and other salespeople. As a SAS user, I needed an interpreter for the SAS language, and WPS has more packages and a lower price than any other company I could find, so I decided to go with
it.

Incentivized

• It's a good platform that has a flexible pricing plan which means that users can get hands-on service free at the start.
• GoodData provides its users with excellent charts and drill-down analysis which makes complex large data sets so simplified and easy to understand and interpret.
• For me it is so convenient because everything just gets saturated on a single page.

Incentivized

• WPS Analytics is powered with high performance data processing engine.
• Reusable data models save finances and time.
• Self-service data analyzation portals.

Incentivized

• No option to visualise a pin on a map
• Custom metrics and variables can be tricky to get right
• Hard to gauge where you are in terms of workspace data limits
• Adding and removing DB fields from models is not as intuitive as it could be
• Data model loading logs can be quite dense and hard to read, esp. when new
• Setting up models to correctly reference between DB tables takes practise
• No option to limit the amount of data a model loads once the table is included

Incentivized

• Currently, I barely encounter challenges when using WPS Analytics although I don't use it on a daily basis. There's no functionality or feature that needs more improvement.

Incentivized

Each client I have worked with and spoken too has renewed their GoodData subscription. I know of not one to date that has cancelled. The GoodData platform has a very high rate of renewal from the discussions I have had with their internal teams as well

After comparing over 20 solution, this is probably not the best in class but the feature set is very competitive. If budget is of no issue, solution like Looker is probably more popular and robust but if you do not want to spend every bit of your budget just for your BI tooling, most users would find GoodData reasonably good enough especially if you are on the SME level

Incentivized

We are approximately one month since go-live. There has been one short outage.

Performance on refreshing metrics works well.

The fast and comprehensive responses we got from GoodData regarding the doubts we had experienced while starting to use the products and metrics were of great help in ensuring the metrics we were obtaining were accurate to what we wanted to know about our customers' experience and our product areas of opportunity.

Incentivized

Petr was a rock star - patient, knowledgeable, clear and easy to work with.

GoodData implementation team was professional and courteous

Thorough, professional and on time.

We chose gooddata compared to other products because gooddata is easier for ordinary people like me to use. Apart from being easy, gooddata also has many features which are more than enough to help my work and costs incurred by gooddata are lower than when I use other products. Thank you goodata for helping our work

Incentivized

I use a lot of data discovery and visualization tools at workstations to help me gain deep insights into data. WPS Analytics doesn't vary much from all the DVD tools that I have listed, I always go for the best.

Incentivized

• It has helped us drive down support ticket volume
• Better data insights of support tickets helped identify key customer issues and channelize efforts accordingly
• Detailed analysis of existing issue, helped identify product defects across the board thereby provide meaning insights to engineering teams to resolve product issues that were previously unknown to us

Incentivized

• Using machine learning and natural language to analyze data saves time and effort.
• Standard reporting and business intelligence help us reduce workload and make data-driven decisions.
• Drag-and-drop workflow saves time when different languages like SQL and SAS make it easier to code and prepare data.

Incentivized