Ayasdi Core vs. Epicor Grow

Well suited: 1. If data set is not yet well organized. 2. Hypothesis is not yet established. 3. Need to visually explore to find patterns of data (often when analysts have no good understanding of data) 4. When [you need] to analyze events with a timeframe (specifically a sequence of events as a transaction) Less appropriate 1. If a data set is very large, such as Hadoop data, it becomes hard to manage data pipeline and process to feed the data into Ayasdi. To be feed into Ayasdi, data should be aggregated or organized to some level.

Incentivized

Grow.com is well suited if you have a lot of data or client data to manage. If you do not have tons of data, there are other options out there that are a bit more simple and easy to use and a better price.

Incentivized

• Ayasdi Core provides an easy way to get some insight on data. Typically analytics may require having a model or hypothesis before starting to look into the data, but Ayasdi lets you just feed the data first then start seeing what the data looks like.
• Ayasdi Core's topological network visualization is quite unique. It allows you to explore patterns and potential relations between multiple data elements. A user can also dynamically navigate data with different aspects on the web.
• The Web version of Ayasdi is easy to use, stable, and fast. It hasn't crashed even when we feed it a lot of data sets, although it took time.

Incentivized

• I love the fact that you have a team of developers who can help me build metrics or fix metrics that I do not create properly. I had to learn SQL in order to really build the metrics that mattered, which was a lot of fun, but resulted in many broken metrics. The vendor's team was great in responding to me requests for help!
• Really, really appreciate the fact that Grow has SQL formulas to reference when building metrics. Again, as a novice, this accelerated my ability to learn and not have to leave your site and resources and stay within the Grow web properties.
• Great account managers who check in regularly and are willing to help out whenever needed.

Incentivized

• Use of Python SDK is required to feed data into Ayasdi, but it lacks training materials or sample codes for a novice to get started.
• Although Web UI of Ayasdi is looking good, often it freezes when the user runs an analysis. It doesn't crash but the web page needs to be refreshed to see the progress of analysis.
• Algorithms provided by Ayasdi, such as metrics types, lens types need to be explained (what they are and what their strengths and weaknesses are). We had to Google or do research on our own to understand what they are.

Incentivized

• There are basic labeling issues with some of the graph types. Wish there was more customizability here, especially on complex graphs.
• Could help more with analysis of data and trends, but that's going into full-fledged BI territory.
• The functionality of being able to snapshot data isn't quite there.

Incentivized

This tool is definitely a little bit difficult to be able to figure out at first, but after some time of learning you can definitely pick it up. I do wish there were more resources online that would be able to help speed up the learning process

Incentivized

The support team is very helpful and in every situation we have needed help in, they have been able to assist. So I have had a good experience with them

Incentivized

We had a working group that has been using R studio for the general purpose of statistical analysis in our organization. Although it is a great tool that provides enriched function sets, it is time-consuming for our clinical analysts to learn the tool to see the first result. R is somewhat of a developer-oriented/friendly tool. Ayasdi is friendly to a domain analyst or end users. Plus, support and consulting from Ayasdi were excellent so that we could get knowledge from them immediately whenever we needed.

Incentivized

Grow doesn't have as many advanced analytics features and other capabilities as some other 'dashboard' platforms on the market. Simply, if you want a tool for internal use only that has high-level analytics capabilities (regressions, completely custom visualizations, modeling), Grow probably isn't the platform for you. To put it another way, if you have a team of data engineers and scientists doing complex analysis, Grow might not make the most sense. However, if you understand the value of data/visualization/dashboards, but lack some of those skillsets in your company, Grow might be the perfect fit. Not only is it incredibly scalable and reasonably priced compared to other market solutions, but their transform capabilities really stand out. They have many native data transformations that mimic SQL coding of a dataset, without requiring any knowledge of SQL. They've converted these transformations to easy-to-use tools in the platform, which are perfect for the less-technical user.

Incentivized

• Made it so much easier and faster to access data across tools
• Lessened the time exporting and uploading data to excel/sheets for analysis
• Made data and metrics more easily accessible to others in our orgs

Incentivized