Release Date: Dec 24, 2018

EI Related

Report Load Optimization

We have rolled out a major optimization in the report load time on EI. 

Qserver Optimization

The impact on report load time on an average reduced to ~50%.

Please see the GA numbers below:


We have done optimization to use Databricks for Query Server. This is deployed on Apac2 cluster. We achieved ~70% reduction in Avg. Report Load time with this.


Scorecard Table Download (#Jewel Corner)

Scorecard Tables on UI will come as Table in downloaded excel files as shown below:

% in Excel Download (#AFG)

For % type KPIs download excel will show % symbol:

Rename KPIs

We have given a configuration to rename KPIs on the UI. Till now this was done by Tech team. But going forward, Capillary Users or BI POC user would be able to configure this for the org.

Limit number of Active Segments

We have limited the number of Active SCD segments at any point of time to 5 the New Segmentation Engine. There is no limit on Non SCD segments right now. This would allow us to keep only fresh segments activated at any point of time.

Data Export Related

Password Protected CSV

Password Protected CSV files are supported now.

File Path Selection for CSV

Inside Modify Template Screen, one can select a custom path where the exported file needs to be dumped. 

Event Date/ Auto Update Date Selection

Now we can decide if we want to export the data based on Last updated Date or Event Date. This would help in scenarios to get all the registration dump for yesterday. 

Release Date: Dec 6, 2018

Essential Insights

Favorites and Recently Accessed Reports

  • Mark reports as favorite/star to make them appear on the left navigation pane for easy accessing. A user can have up to five Favorite Reports.
  • All the recently accessed reports appear on the All Reports Page. 
  • This would help in optimizing the User Experience with growing set of reports.

KPI Variable Support

  • Variables on KPI to allow us to make generic KPIs and set different values per report or organization. 
  • This would incorporate Ad-hoc analysis
  • Various usecases can be covered using this like:
    1. SMS Cost - varies per brand
    2. Multi-Visit - Now we can define number of visits to consider a customer to be multi-visit
    3. Top N % KPIs: N can be configured.
    4. Business Hours

Explore Mode (Adhoc Analytics)

Library (Default Value for Org)

Points Credit Standard Report

A standard Report for Points Credit is defined. 

VM Uptime Standard Report

A standard report for VM device Uptime monitoring.

Scheduled Report Download Optimization

There is an optimization in place which would decrease the download time for scheduled report. This works based on access pattern, so the users who regularly access schedule reports will get the report quicker

Spot Nodes and Time based Cluster Scale Up and Scale Down

We are scaling up the clusters based during business hours and it down post business hours. This would allow to reduce the lag due to heavy traffic during business hours.

Moreover, in case of high traffic, we are adding spot nodes(more compute) to clusters on demand to provide optimum experience.

CMT Filters

Custom Field Filters

We have released the support for filters on custom fields. This is string bases filters and support "starts with", "ends with" and "contains" operators.

Data Export

Duplicate Schedule

We have released support for copying an existing schedule. This would allow to quickly replicate the same schedules over and over again.


Market Basket Analysis

We have released a Notebook to achieve Market basket Analysis for any brand. The notebook is attached with this mail and can be imported into Zepplin. Apriori Algorithm is used. For further details for this please reach out to @Varun Veddu  or @Jyotiska Bhattacharjee.

In market basket analysis (also called association analysis or frequent itemset mining), you analyze purchases that commonly happen together. For
example, people who buy bread and peanut butter also buy jelly. Or people who buy shampoo might also buy conditioner. What relationships there are between items is the target of the analysis. Knowing what your customers tend to buy together can help with marketing efforts and store/website layout.

External Data Ingestion in Zepplin

We have released support to ingest external data in Zepplin. This would allow to reduce dependency on Qubole and allow adhoc analysis on external data. Details of the same can be found here.