Ayasdi Core vs. Kyvos Semantic Layer

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

Kyvos Insights has made it simple for us to work with all our customer data. Now, we get a clear picture of how we’re doing across locations and products, all thanks to its performant tech. It's the only tool that allowed us to explore five years of data and get answers quickly.

• 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

• Easy to integrate with existing tech stack.
• It is easy to make big complex queries and minimal processing time.
• Good customer support and customization support from customer service team.

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

• We’re able to add more dimensions and measures to our reports without performance issues. Another great advantage of Kyvos Insights was the capability to migrate our workloads to GCP.

Incentivized

Kyvos has made a big difference by enabling fast data processing and interactive reporting. It has significantly reduced the time needed to gain insights and made it easier to expand our data operations without slowing down, greatly improving our efficiency.

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

to be honest we used all these platform along with Tableau. Its just each of them fulfil different use cases. Kyvos Insights is more about a platform to with with big data for investigations.

• We’d love more customization options to adapt the platform to our specific needs. The initial setup was also a bit tricky, but once done, it runs smoothly.