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Snowflake Time Travel: How to Leverage it to Achieve Optimal Results
30 May 2023 
Sumi S Benefits of Snowflake Time Travel
With Snowflake Time Travel, you can access historical data, including data that has been altered or deleted, at any given point. This feature is helpful for various tasks, such as:- • Querying data that has been modified or erased in the past
- • Duplicating entire tables, schemas, or databases at or before specific dates
- • Restoring deleted tables, schemas, and databases
How to activate Snowflake Time Travel?
Activating Snowflake Time Travel is a simple process that requires no additional effort. It is automatically activated with a retention period of one day. Nonetheless, upgrading to the Snowflake Enterprise Edition is necessary to customise the Data Retention Period and extend it to 90 days for Databases, Schemas, and Tables. It's important to note that increasing the Data Retention Period results in additional storage usage, reflected in your monthly Storage Fees.
Data Retention Period in Snowflake
In Snowflake, Data Retention Period determine how long historical data is retained to support Time Travel functionality. When data in a table is altered, such as through deletions or updates, Snowflake maintains the previous state of the data so that Time Travel operations (like SELECT, CREATE...CLONE, UNDROP) can be performed on it. By default, all Snowflake accounts have a standard retention period of one day (24 hours).
However, the Retention Period can be adjusted at the account and object level in the Snowflake Standard Edition to 0 (or unset to the default of 1 day) for databases, schemas, and tables.
In the Snowflake Enterprise Edition or higher, the Retention Period can be set to 0 for temporary databases, schemas, tables, and temporary tables. For permanent databases, schemas, and tables, the Retention Time can be configured to any duration between 0 and 90 days.
Functions of Snowflake Time Travel SQL Extensions
Snowflake Time Travel SQL Extensions are special SQL commands that allow users to query historical data from a specific point in time using the Time Travel feature. These extensions enable users to perform various Time Travel operations, including:
- a. CLONE: This command creates a copy of a table, schema, or database at a specific point in time using Time Travel.
- b. UNDROP: This command restores a dropped table, schema, or database to a specific point in time using Time Travel.
- c. HISTORY: This command retrieves the history of changes made to a table, schema, or database over time using Time Travel.
- d. AS OF: This command retrieves data from a table as it appeared at a specific point in time using Time Travel.
Specifying a Custom Data Retention Period for Snowflake Time Travel
To specify a custom Data Retention Period for Snowflake Time Travel, you can use the DATA_RETENTION_TIME IN_DAYS argument in the command when creating a table, schema, or database. By default, the maximum Retention Time in Standard Edition is set to 1 day (i.e. 24 hours), while in Snowflake Enterprise Edition (and higher), it can be set to any value up to 90 days.
The Data Retention Time can be set in the way it has been placed in the example below.
To create a schema with a custom Data Retention Period of 60 days, you can use the following SQL command:
create table mytable(col1 number, col2 date) data_retention_time_in_days=60;
Modify the Data Retention Period for Snowflake Objects
To modify the Data Retention Period of a Snowflake object, any change made to the Retention Period affects both active data and data in Time Travel. Depending on whether the period is increased or decreased, the following impacts occur:
- a. Increasing Retention
- b. Decreasing Retention
Let’s dive deep into more details:
a. Increasing Retention
Snowflake Time Travel preserves the data for a more extended period. For instance, if a Table’s Retention Time is increased from 10 to 20 days, the data set to be deleted after ten days will be retained for an additional ten days before being moved to Fail-Safe. However, data over ten days old and already transferred to Fail-Safe mode is unaffected.
b. Decreasing Retention
The duration of data stored in Time Travel is reduced. The shorter Retention Period applies only to active data updated after the Retention Period is shortened. If the data is still within the new Retention Period, it stays in Time Travel; otherwise, it is placed in Fail-Safe Mode. For instance, if a table with a 10-day Retention Period is reduced to 1 day, data from day 2 through day ten will be transferred to Fail-Safe, and only data from day one will be accessible through Time Travel.
Since the background process moves the data from Snowflake Time Travel to Fail-Safe, it may take some time to see the changes. Although Snowflake guarantees that the data will be transferred, it does not specify when the process will be finished. The data remains accessible via Time Travel until the background process is completed.
To change an object's Retention Period, use ALTER object command, such as the following command for modifying a table's Retention Period:
alter table mytable set data_retention_time_in_days=30;
Snowflake Time Travel Data Query
To query previous versions of data in Snowflake Time Travel, you can use the AT | BEFORE Clause after making any DML actions on a table. This clause allows you to query data at or before a certain point in the table's history throughout the retention period. The specified threshold can be either time-based (e.g., a timestamp or time offset from the present) or a statement ID (e.g., SELECT or INSERT).
For example, to select historical data from a table as of a specific date and time, you can use a query like:
sql
SELECT * FROM my table AT (TIMESTAMP => 'Fri, 05 May 2023 16:20:00 -
If you want to pull data from a table that was last updated a certain number of minutes ago, you can use a query like:
sql
SELECT * FROM my_table AT(OFFSET => -60*5);
And to collect historical data from a table up to a specified statement's modifications, but not including them, you can use a query like:
Sql
SELECT * FROM my_table BEFORE(STATEMENT => '8e5d0ca9-005e-44e6-b858-a8f5b37c57
How to Restore Deleted Objects by Utilising the UNDROP Command?
To restore a deleted object that hasn't been permanently removed from the system (meaning it can still be seen in the "SHOW object type> HISTORY" output), you can use the UNDROP command in conjunction with Snowflake Time Travel. This command can be applied to various objects, such as tables, schemas, and databases. It effectively reverts the thing to its previous state before it was deleted with the DROP command. For example, the UNDROP command can also restore a dropped database.
Summing Up
Snowflake Time Travel’s features can enhance your decision-making process and overall data experience. If you're looking for a Snowflake service provider, Beinex is an excellent option. Our partnership with Snowflake enables us to offer advanced features like automated tuning, elastic compute, and analytics modernisation services to help your organisation realise exponential Returns on Investment.
The Snowflake Time Travel is a fascinating tool that enables users to retrieve data from any previous moment. For instance, if someone accidentally deletes an employee table, they can use Time Travel to go back in time by five minutes (up to 90 days) and recover the deleted data.
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How Atlantis Dubai Standardized Interactive Data Visualization By Implementing The Tableau Server Platform On AWS That Drove Faster and Smarter Decisions Leading to 11 Increment In H
While sharing the content, permissions can be given to each user that restricts them from editing, applying different types of filters, and sharing it further. Users can create apps and add specific visuals to create live dashboards that can be accessed through smartphones and tablets. Moreover, one can collaborate with other designers and administrators to work together and create highly customized reports for a particular field.
Challenge
- The IT infrastructure of Atlantis where the Tableau Server platform was hosted was in an on-premise datacenter which was designed to be scalable and robust with multi node physical clusters including the server, storage and network components. However, most of the physical hardware was quite old and not equipped with the latest generation of physical servers.
- Frequent hardware crashes and portal downtime kept troubling the availability of the Tableau Server application. Assigning a touch hand support person to power on the hardware that was down seemed quite impossible due the restrictions during covid period. Hence, Atlantis wanted to look for another viable solution.
- Though the hardware setup at Atlantis was well equipped to meet the occasional spikes in the traffic, it was observed that over a course of 6-month time, most of the IT infra was underutilized than predicted. It was realized that spending huge amount of money on an old hardware plus software maintenance, license costs, internet bandwidth, datacenter cooling and maintenance, touch support personnel and electricity costs – were keeping the business operations challenging.
- There was an attempt by Atlantis to select a cost-effective solution that can host Tableau Server application servers, web servers and archival data. This way IT infra can be re-provisioned to host sensitive data on-premise and the rest on the cloud, thereby reducing the overall physical hardware costs spent on a yearly basis.
Why AWS
- Atlantis decided to migrate Tableau Server, database servers, and archival data to AWS.
- The Tableau Server’s AWS architecture includes Amazon Elastic Compute Cloud (Amazon EC2), that provides complete control of its computing resources, updates to tables in Amazon Relational Database Service (Amazon RDS) and AWS Elastic Load Balancer was used to distribute the traffic to the underlying EC2 instances based on the load.
Benefits
- Atlantis uses AWS services to provision infrastructure and deploy the Tableau Server platform to other departments within it. In addition, the Tableau Server resources that are no longer required to be run all the time are made to auto shutdown thus saving cost. Atlantis reported a 28% cost reduction after implementation of AWS for the Tableau Server platform.
- The implementation of Tableau Server on AWS made Atlantis confident in the security of its data, and its accreditation team is enthusiastic about the monitoring and auditing capabilities provided by AWS tools. With the implementation of IAM roles, Atlantis IT team was able to isolate systems and tightly control user accesses. These capabilities were harder to achieve within the existing infra but were available out of the box with AWS
- By adopting AWS to host the Tableau Server platform, Atlantis has been able to innovate and experiment to a degree previously impossible. For example, Atlantis compared the performance and cost-effectiveness of three different cloud solutions. Without moving to the AWS, the costs associated with running an outdated on-premise hardware would have creeped up and the alternative way of upgrading the existing on-prem infrastructure to the latest hardware models and then hosting the Tableau Server application on top of it would have taken months.
ASK DATA: TABLEAU’S NEW NATURAL LANGUAGE
Ask Data: Tableau’s New Natural Language Capability Engine
Hello Tableau Fans! As promised here is the blog about the most awaited feature of Tableau 2019.1, ASK DATA! I have been waiting for this since the day it was announced in beta. Now it’s available with 2019.1 version on server and online. For those who don’t know what AskData is, its natural language capability engine integrated within Tableau server and Online. It takes self-service analytics to next level by allowing end users to get answers to their questions by simply typing. All we need to do is curate the dataset to make it easy for end user, publish it and start questioning.
Although it gives you powerful ability to bring out the insights, data also needs to be curated in a way that end user can easily understand and make use of it. Key points to keep in mind when you publish the data source for AskData.
I’m using sample super store to show AskData in action. Below shows how the aggregation works and how easily data fields can be changed on the fly.
It also leverages the ShowMe functionality that’s already available to change the type of chart. It lists down all the available charts based on your data fields. You can also observer the suggestions by NLP while you type questions. You can click on the one which is more relevant to your question.
It’s obvious that users tend to enter similar words while asking these questions. For example, they might type products instead product names. We can create synonyms for the data fields, so that it understands the question better. It takes no time to do this.
It understands all your questions and takes the advantages of existing analytical capabilities like aggregation, sorting, filtering, etc. It does auto-sorting when you select a bar chart.
AskData ships with a very powerful algorithm which understands the data, automatically indexes and gives you the right viz for your question. Here are some best practices to make it more useful.
In conclusion, AskData will certainly change the way we interact with data by shortening the time taken for data driven decisions.
I hope you have enjoy reading my blog, please keep up with us as we will be adding many more!
Please contact us at info@beinex.com to schedule a Tableau demo or training for you or your company.
Try to limit data fields as less as possible where it supports up to 1000 data fields.
Create hierarchies to give drilldown and drill up flexibility to users.
Rename the fields to make it more relevant and meaningful
Be cautious when using geographical data. Make sure to map the geo codes properly.
Create calculated fields if necessary.
Curate your data source keeping the end user in mind
Create all the calculations and synonyms before exposing to end user
Apply your existing governance and access to the published data source.
Keep your question short
Beinex Bags the Title: Best in Data & Analytics at the 12th Edition of Digital Transformation Summit, UAE
Under the thematic area of “Decoding Barriers to Pave the Way for UAE’s Digital Future”, Digital Transformation Summit brings together UAE’s 200+ CTOs, CIOs, CISOs, heads of digital transformation, IT infrastructure, cyber security, information and communication technologies and other experts in the domain.
Beinex is a multinational firm exploring the endless possibilities of data for Cloud, Analytics, Artificial Intelligence, Machine Learning, and Automation.
Partnerships are what make Beinex stronger. The company has solid partnerships with some of the leading technology firms, research labs, and universities around the globe. Beinex has robust, substantive business alliances at multiple levels with Microsoft, Salesforce, AWS, Tableau, Alteryx, Snowflake and other leading techno-ecosystems.
By virtue of these partnerships and its constant urge to drive past excellence benchmarks, Beinex became a deserving candidate to win this prestigious award.
And the Award Goes to Beinex
In effect, Beinex architects, guides, leads, and implements solutions in Analytics, AI, and ML for the spheres of Digital Transformation, GRC, and Risk & Audit Transformation. Present in three continents, Beinex enables its clients to analyze data, mitigate risks, identify opportunities and automate processes.
The award recognizes the relentless pursuit of excellence by Team Beinex in the domains it is into.
“It is a moment of pride and happiness for Beinex. The award secured in the Best in Data & Analytics category at the Digital Transformation Summit, UAE, 2022, is a testimony to the fact that Beinex has continuously and without fail pursued business excellence powered by innovation and experience. We acknowledge and understand that with great recognition comes responsibilities of a greater degree, a calling of a higher order. And we will continue to honor and live up to them. On this joyous occasion, I would love to thank Team Beinex for what they have achieved! This award belongs to them”, noted Indumon Das, the Founder & Managing Director, Beinex.
Beinex Holdings is a group of six companies. As an organization, Beinex believes in the power of ideas, innovation, and unparalleled customer service to change the world for good. Beinex Digital, a part of Beinex Holdings, is a digital transformation entity with a comprehensive suite of independent products focused on addressing specific business gaps, use cases, and needs.
It incorporates a spectrum of solutions related to employee health and safety, enterprise product management, performance management, and audit & risk management.
To Faster Insights and Beyond With Tableau 2021.1
Recognized as a leader in analytics and business intelligence platform for 9 consecutive years in Gartner Magic Quadrant, Tableau has a variety of options when it comes to analytics and visualizations and according to me, it keeps getting better and better with every update. The latest 2021.1 update comes packed with some impressive features and these are some of them that caught my eye:
Quick LODs
LOD calculations are frequently used in Tableau to perform calculations on a fixed dimension. Where previously I had to mention the dimension to be fixed and the measures to be aggregated in a calculated field, now all I must do is select the dimension and measure in the data pane and right click to create an LOD calculation. Or even better, hold “Ctrl” to drag and drop the required measure field onto the dimension to be fixed. As simple as that.
I can modify the calculation with more dimensions or change the type of aggregation later, if required.
This feature is most beneficial as it reduces the chance of errors while creating complex LOD calculations, like misplacing a bracket, or adding any unnecessary characters by mistake.
More Data Connections
With the increase in popularity of Microsoft Azure services among users, Tableau has added multiple Azure connectors including Azure SQL Database and Azure Data Lake Gen 2 along with the existing Azure Synapse Analytics and Databricks. I can now connect to data that is stored in Azure’s SQL Database and Data Lake using the native Tableau connectors. Tableau has also introduced authentication to Azure services using the Azure Active Directory, making the connection more secure.
In addition to this, four new data connectors have been added to Tableau Online and Tableau Server. They are Amazon Athena, Apache Drill, OData and SharePoint Lists.
View Metrics
A difficulty that I had faced with the metric feature was that I was not able to know the other metrics that were created in the same dashboard. With this update I can see all the metrics associated with a particular dashboard and modify these metrics if required or create new ones within the metrics pane.
And previously, only if my site role were “Creator” or “Explorer”, I could see the metrics. But in this update, I can see all metrics connected to a dashboard irrespective of my site role.
Dashboard Extensions in Tableau
Earlier, to use an extension in a Tableau Dashboard, I had to drag and drop the extension object on the dashboard which would take me to its extension gallery web page and then I had to download it and then locate the downloaded extension on Tableau. Sounds tiring right?
Not anymore! With this update, all I have to do is drag and drop the extension object onto the dashboard to select the required extension. I can now see all extensions and filter the list based on categories within the “Add an Extension” window in the Tableau screen.
Write to Excel in Tableau Prep
This is one feature that will prove useful to any regular Tableau Prep user. The days of exporting an output to csv and then converting it manually to an xlsx file are finally over.
Using the latest version of Tableau Prep, I can directly export the output of a workflow into an xlsx file.
Device Designer for Web Authoring
Where before I could only generate device specific layouts in Tableau Desktop, now I can create custom phone or tablet views within the web itself. I no longer have to modify the device layout in Tableau Desktop and re-publish whenever a change in device layout is required.
Licensing Improvements
With this update, Tableau has introduced zero downtime licensing for the Tableau Server. Now for most of the tasks, whether it is the activation of a license or updating a feature that got added or applying some changes to user capacity, I no longer need to perform a server restart.
So, these are some features that have been helpful to me and these are just a few of the lot. To view all the new features in 2021.1, you can view it at Tableau 2021.1 New Features
In my view, Tableau has done a great job with its timely and inventive updates and seeing the rapid growth of AI and the increase of its application in numerous industries, I can predict for sure that Tableau will surprise the data science community with more innovative updates.
Images Courtesy: Tableau
- Einstein Discovery
- Quick LODs
- More Data Connections
- View Metrics
- Dashboard Extensions in Tableau
- Write to Excel in Tableau Prep
- Device Designer for Web Authoring
- License Improvements
- Through Dashboard Extensions: To use “Einstein Discovery” in dashboards, I can just add an extension object on the dashboard and select Einstein Discovery. It will analyse the selected data and build predictive models. It shows me the top predictors in the view along with metrics that can be improved, and thus helping business decisions. This feature is available in Tableau Desktop, Tableau Server and Tableau Online.
- Through Analytics Extension: With this feature, I can directly embed predictions into Tableau calculated fields. All I have to do is go to Salesforce, use Model Manager to generate a Tableau table calculation script and paste the script into the calculated field in Tableau. This script then accesses predictive models in Salesforce by passing the data required for the model. This saves my time since I don’t need to create a code for the model. This feature is only available in Tableau Desktop and Tableau Server.
- Through Tableau Prep: This feature was released in 2021.1.3 and its ingenuity is worth mentioning. With “Einstein Discovery” in Tableau Prep, I can now use predictions while preparing data. I can bulk score my data and create fields to show prediction outcomes, to show top predictors and to show recommendations for improvement of the output.
Quick LODs
LOD calculations are frequently used in Tableau to perform calculations on a fixed dimension. Where previously I had to mention the dimension to be fixed and the measures to be aggregated in a calculated field, now all I must do is select the dimension and measure in the data pane and right click to create an LOD calculation. Or even better, hold “Ctrl” to drag and drop the required measure field onto the dimension to be fixed. As simple as that.
I can modify the calculation with more dimensions or change the type of aggregation later, if required.
This feature is most beneficial as it reduces the chance of errors while creating complex LOD calculations, like misplacing a bracket, or adding any unnecessary characters by mistake.
More Data Connections
With the increase in popularity of Microsoft Azure services among users, Tableau has added multiple Azure connectors including Azure SQL Database and Azure Data Lake Gen 2 along with the existing Azure Synapse Analytics and Databricks. I can now connect to data that is stored in Azure’s SQL Database and Data Lake using the native Tableau connectors. Tableau has also introduced authentication to Azure services using the Azure Active Directory, making the connection more secure.
In addition to this, four new data connectors have been added to Tableau Online and Tableau Server. They are Amazon Athena, Apache Drill, OData and SharePoint Lists.
View Metrics
A difficulty that I had faced with the metric feature was that I was not able to know the other metrics that were created in the same dashboard. With this update I can see all the metrics associated with a particular dashboard and modify these metrics if required or create new ones within the metrics pane.
And previously, only if my site role were “Creator” or “Explorer”, I could see the metrics. But in this update, I can see all metrics connected to a dashboard irrespective of my site role.
Dashboard Extensions in Tableau
Earlier, to use an extension in a Tableau Dashboard, I had to drag and drop the extension object on the dashboard which would take me to its extension gallery web page and then I had to download it and then locate the downloaded extension on Tableau. Sounds tiring right?
Not anymore! With this update, all I have to do is drag and drop the extension object onto the dashboard to select the required extension. I can now see all extensions and filter the list based on categories within the “Add an Extension” window in the Tableau screen.
Write to Excel in Tableau Prep
This is one feature that will prove useful to any regular Tableau Prep user. The days of exporting an output to csv and then converting it manually to an xlsx file are finally over.
Using the latest version of Tableau Prep, I can directly export the output of a workflow into an xlsx file.
Device Designer for Web Authoring
Where before I could only generate device specific layouts in Tableau Desktop, now I can create custom phone or tablet views within the web itself. I no longer have to modify the device layout in Tableau Desktop and re-publish whenever a change in device layout is required.
Licensing Improvements
With this update, Tableau has introduced zero downtime licensing for the Tableau Server. Now for most of the tasks, whether it is the activation of a license or updating a feature that got added or applying some changes to user capacity, I no longer need to perform a server restart.
So, these are some features that have been helpful to me and these are just a few of the lot. To view all the new features in 2021.1, you can view it at Tableau 2021.1 New Features
In my view, Tableau has done a great job with its timely and inventive updates and seeing the rapid growth of AI and the increase of its application in numerous industries, I can predict for sure that Tableau will surprise the data science community with more innovative updates.
Images Courtesy: Tableau
Tableau 2021.2 : New Features
This has changed the way we interpret information by giving us a look into past insights but also to forecast future events, allowing us to make informed decisions.
Tableau 2021.2. includes ‘ask and explain data’ for viewers, allow connected desktops, Collections, and many more valuable features. Some of the key enhancements are listed below.
Collections provides a new format to organize content across your sites on both Tableau Online and Server into manageable folders. You may group item together from different projects and workbooks and you can reuse content in multiple contexts without additional storage or resources. Collections also makes it easier to share content around a central theme. For example, you can create a “Daily Sales” collection that includes dashboards with daily sales statistics, ETL data flow, data sources, etc.
Collections helps you congregate your data. You are given the leeway to create, explore and save your content privately. Another key feature of ‘Collections” is that users can create customized collections which are by default private. However, you are given the option to share the collection with any authorized users you choose to provide access to.
1) User Management Enhancement
In earlier versions, a subscribed user, deleted by an admin, was not erased from the system entirely. They were then classified as an 'unlicensed user'.
With version 2021.2, the subscribed creator will be deleted automatically when an admin deletes a user either via the UI or the REST API, without the extra step of reassigning the subscription ownership.
2) Ask Data Enhancements
Ask Data Lenses
A new feature introduced with this update is 'Ask Data Lenses'. It allows for easy data curation with defined columns and value synonyms and also provides suggested questions to allow for more inclusive data from a variety of sources.
(The update brings a new content type that is Ask Data Lenses, making it easy to curate data with the definition of column and value synonyms and suggested questions so you can better leverage existing published data sources.)
They are created alongside published data sources Ask Data use case(s) while maintaining the underlying data source as its own entity.
These 'lenses' are comparable to ‘views’. For those of you who are adept with SQL, where you can write selected statements specifically to extract the required columns, give definitions, whilst maintaining the integrity of the data source. Similarly, once created, ‘lenses’ can be accessed by viewers, opening Ask Data to a new class of users that struggle to self-serve their needs today.
Entity Search
Entity Search shows users search results of keywords, like the Google search box. Ask Data gives you word-by-word search results, giving you instant feedback on your data and what Ask Data can do. Ask Data will automatically choose the most relevant interpretation of your search and these search results help you build that input more effectively by selecting the right fields and values in the data set. Ask data learns from your selections to choose smarter defaults for future searches.
MFA allows users to easily add an additional layer of security to their accounts.
This feature unlocks the ability for Tableau Online customers who utilize native Tableau ID authentication to enforce multi-factor authentication (MFA) when their users sign into their sites. End-users can use applications like Salesforce Authenticator or Google Authenticator to perform additional verification of their identity when they log on to Tableau.
MFA makes it much harder for common threats like phishing attacks and account takeovers to succeed. MFA is one of the easiest and most effective ways customers can enhance login security and safeguard their business and data against external threats.
Easily rename multiple fields in prep allows creators to transition seamlessly from web authoring to Tableau Desktop with a single click of a button. Creators will now be able to edit any workbook that they have permission to on Desktop.
Prior to 2021.2, users had to manually change each header name. For example, if a user wanted to change “Customer” at the start of multiple header names, they would need to click on each field name and individually change/remove “Customer” in the field name. Not a big deal when there are less than 10 columns to update. However, for customers with data sets of 50+ columns, it is more cumbersome to have to individually change each field name. This feature allows a customer to quickly add a prefix, rename or add a suffix to multiple fields collectively.
Tableau Prep is expanding its output capabilities to include Google BigQuery, enabling you to add or update data in Google BigQuery with clean, prepped data from your flow each time it is run.
TABLEAU DESKTOP 2020.2 – Key Features
1) Maps: Spatial File Support
The Marks Layers Control SP1 feature provides a control that allows users to toggle the visibility of layers on a map viz. The control works like a filter and the user is free to choose which layer(s) to view in order to answer their question. In addition, the user can control the interactivity of the map viz by selectively enabling or disabling selection on the layer in question.
Toggle button – Our users can now use a button to show/hide any dashboard zone, floating or tiled. This function was previously limited to floating horizontal and vertical containers only.
URL support for images – Users can now add images via external URLs, which also provides GIF support for images on the internet and workbooks. Loading these images will be time-efficient.