Tellius
  • ๐ŸšฉGetting Started
    • ๐Ÿ‘‹Say Hello to Tellius
      • Glossary
      • Tellius 101
      • Navigating around Tellius
      • Guided tours for quick onboarding
    • โšกQuick Start Guides
      • Search
      • Vizpads (Explore)
      • Insights (Discover)
    • โœ…Best Practices
      • Search
      • Vizpads (Explore)
      • Insights (Discover)
      • Predict
      • Data
    • โฌ‡๏ธInitial Setup
      • Tellius architecture
      • System requirements
      • Installation steps for Tellius
      • Customizing Tellius
    • Universal Search
    • ๐Ÿ Tellius Home Page
  • Kaiya
    • โ™Ÿ๏ธUnderstanding AI Agents & Agentic Flows
      • Glossary
      • Composer
      • ๐Ÿ—๏ธTriggering an agentic workflow
      • The art of possible
      • Setting up LLM for Kaiya
    • ๐ŸคนKaiya conversational AI
      • โ“FAQs on Kaiya Conversations
      • Triggering Insights with "Why" questions
      • Mastering Kaiya conversational AI
  • ๐Ÿ”Search
    • ๐Ÿ‘‹Get familiar with our Search interface
    • ๐Ÿค”Understanding Tellius Search
    • ๐Ÿ“Search Guide
    • ๐Ÿš€Executing a search query
      • Selecting a Business View
      • Typing a search query
      • Constructing effective search queries
      • Marketshare queries
    • ๐Ÿ”‘Analyzing search results
      • Understanding search results
      • Search Inspector
      • Time taken to execute a query
      • Interacting with the resulting chart
    • ๐Ÿ“ŠKnow your charts in Tellius
      • Understanding Tellius charts
      • Variations of a chart type
      • Building charts from Configuration pane
      • List of chart-specific fields
      • Adding columns to fields in Configuration pane
      • Absolute and percentage change aggregations
      • Requirements of charts
      • Switching to another chart
      • Formatting charts
      • Advanced Analytics
      • Cumulative line chart
    • ๐Ÿง‘โ€๐ŸซHelp Tellius learn
    • ๐Ÿ•ต๏ธโ€โ™‚๏ธSearch history
    • ๐ŸŽ™๏ธVoice-driven search
    • ๐Ÿ”ดLive Query mode
  • ๐Ÿ“ˆVizpads (Explore)
    • ๐Ÿ™‹Meet Vizpads!
    • ๐Ÿ‘‹Get familiar with our Vizpads
    • #๏ธโƒฃMeasures, dimensions, date columns
    • โœจCreating Vizpads
    • ๐ŸŒApplying global filters
      • Filters in multi-BV Vizpads
      • Filters using common columns
    • ๐Ÿ“ŒApplying local filters
    • ๐Ÿ“…Date picker in filters
      • Customizing the calendar view
    • โœ…Control filters
      • Multi-select list
      • Single-select list
      • Range slider
      • Dropdown list
    • ๐Ÿ‘๏ธActions in View mode
      • Interacting with the charts
    • ๐Ÿ“Actions in Edit mode
      • ๐Ÿ—จ๏ธViz-level actions
    • ๐Ÿ”งAnomaly management for line charts
      • Instance level
      • Vizpad level
      • Chart level
    • โณTime taken to load a chart
      • Instance level
      • Vizpad level
      • Chart level
    • โ™Ÿ๏ธWorking with sample datasets
    • ๐Ÿ”Swapping Business View of charts
      • Swapping only the current Vizpad
      • Swapping multiple objects
      • Configuring the time of swap
    • ๐Ÿค–Explainable AI charts
  • ๐Ÿ’กInsights (Discover)
    • ๐Ÿ‘‹Get familiar with our Insights
    • โ“Understanding the types of Insights
    • ๐Ÿ•ต๏ธโ€โ™‚๏ธDiscovery Insights
    • โž•How to create new Insights
      • ๐Ÿ”›Creating Discovery Insight
      • ๐Ÿ”‘Creating Key Driver Insights
      • ใ€ฐ๏ธCreating Trend Insights
      • ๐Ÿ‘ฏCreating Comparison Insights
    • ๐ŸงฎThe art of selecting columns for Insights
      • โžก๏ธHow to include/exclude columns?
  • ๐Ÿ”ขData
    • ๐Ÿ‘‹Get familiar with our Data module
    • ๐Ÿฅ‚Connect
    • ๐ŸชนCreate new datasource
      • Connecting to Oracle database
      • Connecting to MySQL database
      • Connecting to MS SQL database
      • Connecting to Postgres SQL database
      • Connecting to Teradata
      • Connecting to Redshift
      • Connecting to Hive
      • Connecting to Azure Blob Storage
      • Connecting to Spark SQL
      • Connecting to generic JDBC
      • Connecting to Salesforce
      • Connecting to Google cloud SQL
        • Connecting to a PostgreSQL cloud SQL instance
        • Connecting to an MSSQL cloud SQL instance
        • Connecting to a MySQL Cloud SQL Instance
      • Connecting to Amazon S3
      • Connecting to Google BigQuery
        • Steps to connect to a Google BigQuery database
      • Connecting to Snowflake
        • OAuth support for Snowflake
        • Integrating Snowflake with Azure AD via OAuth
        • Integrating Snowflake with Okta via OAuth
        • Azure PrivateLink
        • AWS PrivateLink
        • Best practices
      • Connecting to Databricks
      • Connecting to Databricks Delta Lake
      • Connecting to an AlloyDB Cluster
      • Connecting to HDFS
      • Connecting to Looker SQL Interface
      • Loading Excel sheets
      • ๐ŸšงUnderstanding partitioning your data
    • โณTime-to-Live (TTL) and Caching
    • ๐ŸŒทRefreshing a datasource
    • ๐ŸชบManaging your datasets
      • Swapping datasources
    • ๐ŸฃPreparing your datasets
      • ๐ŸคพActions that can be done on a dataset
      • Data Pipeline
      • SQL code snippets
      • โœ๏ธWriteback window
      • ๐ŸงฉEditing Prepare โ†’ Data
      • Handling null or mismatched values
      • Metadata view
      • List of icons and their actions
        • Functions
        • SQL Transform
        • Python Transform
        • Standard Aggregation
        • Creating Hierarchies
      • Dataset Scripting
      • Fusioning your datasets
      • Scheduling refresh for datasets
    • ๐ŸฅPreparing your Business Views
      • ๐ŸŒŸCreate a new Business View
      • Creating calculated columns
      • Creating dynamic parameters
      • Scheduling refresh for Business Views
      • Setting up custom calendars
    • Tellius Engine: Comparison of In-Memory vs. Live Mode
  • Feed
    • ๐Ÿ“ฉWhat is a Feed in Tellius?
    • โ—Alerts on the detection of anomalies
    • ๐Ÿ“ฅViewing and deleting metrics
    • ๐Ÿ–ฒ๏ธTrack a new metric
  • Assistant
    • ๐Ÿ’Introducing Tellius Assistant
    • ๐ŸŽคVoice-based Assistant
    • ๐Ÿ’ฌInteracting with Assistant
    • โ†–๏ธSelecting Business View
  • Embedding Tellius
    • What you should know before embedding
    • Embedding URL
      • ๐Ÿ“ŠEmbedding Vizpads
        • Apply and delete filters
        • Vizpad-related actionTypes
        • Edit, save, and share a Vizpad
        • Keep, remove, drill sections
        • Adding a Viz to a Vizpad
        • Row-level policy filters
      • ๐Ÿ’กEmbedding Insights
        • Creating and Viewing Insights
      • ๐Ÿ”ŽEmbedding Search
        • Search query execution
      • Embedding Assistant
      • ๐Ÿช„Embedding Kaiya
      • Embedding Feed
  • API
    • Insights APIs
    • Search APIs
    • Authentication API (Login API)
  • โœจWhat's New
    • Release 5.4
      • Patch 5.4.0.x
    • Release 5.3
      • Patch 5.3.1
      • Patch 5.3.2
      • Patch 5.3.3
    • Release 5.2
      • Patch 5.2.1
      • Patch 5.2.2
    • Release 5.1
      • Patch 5.1.1
      • Patch 5.1.2
      • Patch 5.1.3
    • Release 5.0
      • Patch 5.0.1
      • Patch 5.0.2
      • Patch 5.0.3
      • Patch 5.0.4
      • Patch 5.0.5
    • Release 4.3 (Fall 2023)
      • Patch 4.3.1
      • Patch 4.3.2
      • Patch 4.3.3
      • Patch 4.3.4
    • Release 4.2
      • Patch 4.2.1
      • Patch 4.2.2
      • Patch 4.2.3
      • Patch 4.2.4
      • Patch 4.2.5
      • Patch 4.2.6
      • Patch 4.2.7
    • Release 4.1
      • Patch 4.1.1
      • Patch 4.1.2
      • Patch 4.1.3
      • Patch 4.1.4
      • Patch 4.1.5
    • Release 4.0
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ยฉ 2025 Tellius

On this page
  • ๐Ÿš€ New features
  • Metadata for columns
  • Data dictonary for columns
  • Selection of columns for analysis
  • Provision to rank columns
  • Processing of queries on sample data
  • Multi-user subscription to Feed
  • Additional metadata on the Notifications page
  • Subscription to scheduled jobs
  • Kerberos-based authentication for Spark SQL
  • ๐Ÿ“ˆ Enhancements
  • Display of columns in Search and Tellius Assistant
  • โ€˜Weeklyโ€™ aggregation enhancements for date filters
  • Additional treemap algorithms
  • Enriched KPI target chart
  • Vizpads generation on intranet
  • Feature importance of columns
  • Share objects using name
  • Data type of cluster labels
  • Proxy support for connectors
  • Forbidden Python libraries
  • ๐Ÿ› ๏ธ Minor fixes
  • โ›” Deprecation

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  1. What's New

Release 4.1

Released in February 2023

We welcome 2023 with a whole new release! ๐ŸŽ‰ Weโ€™re stoked to announce the latest version of Tellius, 4.1, which comes equipped with a collection of exciting features focused on improving context, collaboration, and visibility. Here is the comprehensive list of features and improvements introduced in 4.1:

๐Ÿš€ New features

Metadata for columns

Understanding the context of every column helps business teams leverage their data and visualize insights faster. So weโ€™ve introduced a metadata view to empower users with an optimal view of all the information about their data in one place.

With this feature, users will be able to add the following types of metadata during data preparation:

  • Column description

  • Display name

  • Data format

  • Data aggregation

  • Data type

  • Include/Exclude columns for Insights and Predict

  • Synonyms

  • Special type

  • Rank

  • Indexing

  • Column type

  • Feature type

Users can easily edit and sort the metadata of each column. The values will be reflected throughout the platform (Search, Insights, Vizpads, Predict, Feed, and Data).

In a dataset, multiple columns can be selected, and changes can be applied to them in bulk.

Data dictonary for columns

Data dictionary is included to help users interpret the context of each column. Across the platform, when a user hovers over a column, its corresponding description and the type of column (measure/dimension) will be displayed in the tooltip. The metadata facilitates business users to be more aware of the descriptions of columns defined in a dataset.

The description of each column needs to be set up in the metadata view during data preparation. Also, the option Show Column Description needs to be enabled under Settings to view the description on contextual tooltips.

Selection of columns for analysis

During data preparation, users have the flexibility to choose the columns to be included for analysis. Every column comes with a toggle option to be included in Insights and Predict. The unselected columns will be excluded from any analysis by default unless modified by the user. The Insight Configuration and Insight Summary will display the list of included and excluded columns along with the reason for exclusion.

Provision to rank columns

During data preparation for live datasets, users can rank the columns (from 1 to 20) to prioritize them over the non-ranked columns. The ranked columns get auto-picked for Live Insights.

If required, a ranked column can still be excluded from Insights or Predict. The ability to rank is unavailable for non-live datasets.

Processing of queries on sample data

Usually, when users create a chart in Vizpad, the results will be rendered for the entire dataset. To avoid the time-consuming overhead of processing large datasets, Tellius introduces a way to run the queries on a limited dataset (sample data). The feature helps save time and makes the overall Vizpad building process more efficient. In the Settings page, admins can enable/disable the option to run the queries on sample data.

The sample data is applicable only while building the Vizpad. Once the Vizpad is saved, the results will be displayed, utilizing the entire dataset.

Multi-user subscription to Feed

Since only the creator of the Feed receives email alerts, Tellius introduces a way for anyone interested in the Feed to subscribe to get regular email alerts. To avoid duplication of Feeds, a new Feed will be created only after checking for any similar Feed. The user can either subscribe to the existing Feed to receive periodic updates or create a new Feed.

Additional metadata on the Notifications page

The Notifications page now displays the metadata (name, type) of every object associated with a job. The metadata enables the user to correlate the type of an executed job with an actual object. If required, users can choose to retry specific failed jobs.

Subscription to scheduled jobs

A new tab has been added to display all the scheduled jobs associated with objects accessible to a user. Users can subscribe to the required jobs to receive regular email notifications. It provides a way to monitor the status (success/failure) of the job and stay informed of the objects shared with them.

Kerberos-based authentication for Spark SQL

Now, users can access Spark SQL tables via Kerberos. In addition to authenticating via username and password, the Spark SQL connector supports Kerberos-based authentication.

๐Ÿ“ˆ Enhancements

Display of columns in Search and Tellius Assistant

To enhance the search experience and help users be more informed of the columns in a business view, the following improvements have been added:

  • Search - When a search query is being typed, the columns present in the corresponding business view will be displayed in the right pane, organized under Group View and Table View. Once a query is successfully executed, the same details will be pinned next to the Search Inspector.

  • Tellius Assistant - Once a business view is selected, the columns will be displayed in the right pane.

Users can show/hide the business view details as required.

โ€˜Weeklyโ€™ aggregation enhancements for date filters

In a Vizpad chart, when users choose a date column with โ€˜weeklyโ€™ aggregation as the dimension, the following improvements will be applicable:

  • The actual weekend dates will be displayed in the chart instead of weekend numbers.

  • A toggle option has been included in the Application Settings to set weekend dates as default when date filters are applied.

Additional treemap algorithms

In a Vizpad chart, users can change the treemap algorithm to represent hierarchical data. Tellius now supports all four algorithms โ€‹โ€‹by Highcharts:

  • Slice and Dice (applied by default)

  • Squarified

  • Stripes

  • Strip

Enriched KPI target chart

To enhance the KPI target chartโ€™s readability, weโ€™ve introduced a way to easily customize and format the font size, font color and style of the following:

  • Measure (title and values) and aggregation

  • Target columns (title and values)

  • Connector text (such as โ€˜ofโ€™)

Users have the flexibility to customize the font size displayed in KPI and KPI target charts using the following two options:

  • Auto-scale - Tellius chooses a responsive sizing based on the size of the chart and length of the text

  • User-defined - The font size set by the user will be considered.

Users can also show/hide aggregation, connector text, and target columns. The text in the chart can be aligned horizontally/vertically and arranged relative/fixed as required.

Vizpads generation on intranet

Tellius has introduced a way to improve the user adoption of Vizpads when they are connected to an on-premises network. Vizpads can be opened seamlessly from scheduled emails when users are logged in to Tellius without an outbound internet connection. The required URLs to be configured are included in Settings to support the rendering of Vizpads and to prevent timeout errors:

Feature importance of columns

A new tab Feature Importance has been added to display the importance of each column. Once a model has been created using XGBoost or regression algorithm, the feature importance would be displayed in percentages as a part of the Model summary.

Share objects using name

Across Tellius, users can now share an object (Vizpad, chart, Insight, Model) by typing in the userโ€™s first name or last name. The email IDs associated with the names would be automatically displayed for more clarity.

Data type of cluster labels

Once clustering is done, the cluster labels will be created with the data type: dimensions (String) instead of measures (numeric) so as to enable users to categorize and visualize data in different charts.

Proxy support for connectors

Tellius now supports proxy configuration to connect with Salesforce and Google Analytics. Users can avail of the optional proxy support to seamlessly load the datasets.

Forbidden Python libraries

The following libraries have been removed and thus cannot be imported into Python during data preparation.

  • shlex

  • sh

  • plumbum

  • pexpect

  • fabric

  • envoy

  • commands

  • os

  • subprocess

  • requests

๐Ÿ› ๏ธ Minor fixes

  1. The Vizpad rendering, loading, and performance issues (side panel, tooltip, CSS, Anomalies, garbage collection) have been fixed and optimized.

  2. The switching between different tabs in a Vizpad has been made seamless, with the warning message displayed only when any changes are made to the current tab.

  3. HTML tags included in the Search queries will be sanitized and rejected with an โ€œInvalid queryโ€ error.

  4. For bar, line, and combo charts, data will not be plotted for null values unless โ€œInclude null valuesโ€ is selected by the user.

  5. The default aggregation set for a column (measure) during data preparation will be reflected across the platform unless modified by the user.

  6. Conditional formatting and number formatting capabilities have been fixed for KPI charts.

  7. The visibility of data labels for the waterfall charts has been rectified.

  8. The dataset renaming issue for DataFusion has been fixed.

  9. Filtering of high cardinality columns using a Vizpad list has been fixed.

  10. The date format displayed in the downloaded Vizpad charts (in CSV format) has been rectified.

  11. The timeout limit for the generation of multiple reports on Vizpad has been increased.

  12. The gaps in email settings and SMTP configurations have been fixed now.

โ›” Deprecation

In the upcoming release 4.2, connecting directly to BigQuery data tables via GCS bucket feature will be deprecated.

PreviousPatch 4.2.7NextPatch 4.1.1

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Metadata
Description for columns
Include/exclude columns in Insight, Predict
Ranked columns in Insights
Sample data
Subscribing to Feed
Metadata on Notifications page
Scheduled jobs tab
Display of columns
Weekly aggregation for date filters
KPI target chart
Vizpads via intranet
Feature importance of columns
Sharing using name
BigQuery via GCS Bucket
โœจ
Applying queries on sample dataset
Include/exclude columns for Insights and Predict
Ranking columns for live datasets
Metadata view
Multi-user subscription to Feed
Scheduled jobs tab
Additional metadata for notifications
Weekly aggregation filters
Displaying columns in a business view
Additional treemap algorithms
Generating Vizpads on intranet
Text formatting in KPI target charts
Feature Importance
Sharing Vizpad using first or last name
BigQuery via GCS
Column description in metadata