Ayasdi Core is a business intelligence software offering from Ayasdi.
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BrightGauge
Score 8.9 out of 10
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BrightGauge is a BI tool from ConnectWise that puts essential information in one place, providing visibility for more informed decisions. The user can customize BrightGauge dashboards and sync other business tools in its BI dashboard software for ultimate visibility. Users can also display data with embeddable gauges on public sites.
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.
I think this tool is an absolute have to have for MSPs, especially those using ConnectWise PSA for a ticketing system. From internal KPIs to showing customer's the value of your Managed Service, you will need this tool. 9/10 because the need for longer data sets is growing for my team. Trend lines over time are a big push industry wide to show improvements in our customers over the time as our MSP customer. Presently my team has to use CW PSA's Report Writer and that tool is the least user friendly we've encountered. Looking forward to the evolution of BrightGauge for our business
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.
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.
Usability is BrightGauge's strength. Granting the ability of virtually any user to be able to create a dashboard is incredibly valuable. If an organization very simple and straight forward reporting needs then BrightGauge is a perfect fit for them. Connecting to the dataset we used was very quick and easy and I imagine it would be the same for any major data source you would like to pull from.
We did not need to use BrightGauge's support for the entire time that we used it. Best support is always the one that isn't needed because nothing breaks.
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.
For larger customers, the dashboarding has helped our customers to remain sticky and add services/revenue to our MSP. They want to add more fragments of their IT for the 1 pane rollup.
From a leadership perspective, BG has allowed me to make difficult staffing decisions with confidence. Detailed metric driven decisions on who is hitting KPIs/who isn't - as well as when data proved we were overstaffed and understaffed.
