Agriculture and the Internet of Things: The Present and the Future

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.

For instance, the dashboard given below mirrors a project undertaken for a client seeking insights into the pandemic's impact on their business across specific areas. They wanted to determine the number of stores stocking their product within a defined radius, highlighting the local business impact amid the pandemic.
To craft the map showcased in this dashboard, we leverage Tableau's map layers feature introduced in version 2020.4. For further insights into this functionality, additional details can be found here.
Prior to initiating the map creation process, frequently refer to the Profit Margin field. Here's the calculation for this field: it computes the percentage of Sales that translates into Profit. This calculation enables us to gauge the profitability derived from our sales figures.
For the States map layer, the State field is utilized and placed on the 'Detail' shelf. Each state is color-coded based on its Profit Margin.
Moving to the Cities layer, the City field is added onto the top left area labeled "Add a Marks Layer." To ensure the visibility of every city, the State level of detail is included as well. This accounts for cities existing in multiple states, displaying every city/state combination. Cities are color-coded using the Profit Margin field, with additional color based on the absolute value of the Profit Margin. This helps visualize the range and direction of profitability for each city.

Buffer Calculation

The Buffer calculation generates a radius, known as a "buffer," around a specific map point, defined within the syntax parameters. Here's the syntax breakdown for the Buffer: The initial part determines the center location, followed by the distance around the point, and finally, the chosen unit of measurement.
To establish the desired centroid point, we employ the Makepoint function. This function simply utilizes latitude and longitude coordinates to generate a point on the map. Below is the calculation illustrating its usage.

To achieve the interactivity you desire, you'll begin by creating three parameters: [Location Lat], [Location Long], and [Radius]. These parameters offer flexibility, allowing you to adjust them within the dashboard interface.
As you click on different cities, the [Location Lat] and [Location Long] fields dynamically change, altering the central point. Meanwhile, the [Radius] field, functioning as an input parameter, enables you to modify the radius distance according to your preferences. This setup grants you personalized control over these parameters directly within the dashboard.

With the creation of the final map layer field, you can now drag this field to the top left of the map and add it to the existing layers. Once done, you'll have all the map layers integrated into the map, allowing you to recreate the dashboard as depicted below. This comprehensive setup will mirror the dashboard layout and functionality.

Parameter Actions

Parameter Actions are essential at this stage to ensure dynamic interaction within the map layers. By implementing parameter actions, we enable the Location Lat and Location Long fields to adjust dynamically when clicking on a city. This action directly affects the MAKEPOINT() field within the Buffer calculation, effectively altering the radius location. Below, you can observe the setup of the parameter action and how it facilitates this dynamic transformation.
Finally, we aim for these parameters to influence the available metrics showcased at the top of the dashboard. These metrics offer insights into the concentration of profit and profit margin within the selected radius. Below, you'll find the supporting calculations and the formulae for the metrics displayed on the dashboard. These metrics serve as indicators of profitability and profit margin concentration within the chosen radius.

Wrapping up, creating interactive data visualizations opens doors to explore and comprehend information, fostering informed decision-making and exploration of new analytical paths.

These services link together all the Snowflake components to handle user requests, from login to query dispatch. The compute commands that Snowflake procured from the cloud provider is also used by the cloud services layer. Every day, Snowflake processes petabytes of data and thousands of customer accounts.

The cloud service layer enables the management of a customer’s account, and it includes:

Authentication

Snowflake allows flexible authentication methodologies like Local, Active Directory, Multifactor and SAML Authentications. It permits the use and maintenance of Snowflake user credentials like login name and password. In short, account and security managers can create users with passwords stored in Snowflake or other authenticators and users can access Snowflake using their login credentials.

Infrastructure Management

With the capacity to immediately spin up and down an almost infinite number of concurrent workloads against the same, single copy of data, the users need not be concerned about the size of the data or the details about how a cluster is powered up instantly, with a few clicks on the corresponding interface. Behind the scenes, the infrastructure manager communicates and provides instructions to the corresponding cloud provider to immediately spin up the resources required by the users.

Metadata Management

Snowflake metadata management is a part of the data governance discipline which involves processes, policies, workflows, and technology to identify, and organise Snowflake metadata for data consumers. Metadata management is the key to adding actionable context to the assets in the Snowflake data warehouse.
Metadata management in Snowflake makes it easy to search, filter, and find data assets by various criteria. Metadata gives you complete visibility into the lifecycle of a data asset. Snowflake stores all the metadata in a centralized component called Cloud Services.
Snowflake automatically creates metadata for data residing both externally (S3, Azure, GCP) and internally (within Snowflake), stores it as a key-value pair (dictionary), and makes it available via the Information Schema.

Query Parsing and Optimisation

Users need not be much concerned regarding query performance. It is handled automatically via a dynamic query optimization engine in the cloud services layer. It can model, load, and query the data.
The cloud services layer does all the query planning and query optimization based on data profiles that are collected automatically as the data is loaded. It automatically collects and maintains the required statistics to determine how to distribute the data and queries most effectively across the available compute nodes.
Snowflake's query caching retains the outcomes of all queries run during the previous 24 hours. The query results returned to one user are accessible to any other user on the system who conducts the same query. It helps to save time by drastically reducing retrieval time when data is pulled from cache memory. The cost is also saved by not spinning up the compute clusters.

Access Control

Access to Snowflake depends on Access Control privileges which determine who can access and operate on Snowflake. According to the Snowflake model, users or other roles with rights allocated to them can gain access to secure items. Every secure object also has an owner who can provide access to other roles. Unlike user-based access control models, which provide rights and privileges to individual users or groups of users, this model does not do it. The Snowflake approach is intended to offer a sizable level of flexibility and control. It enables Snowflake to provide row-level security and protect PII through dynamic data masking.

ZTA in Simple Terms

It is a cybersecurity paradigm focused on enterprise resource protection. This includes data; no matter where it resides, cloud or on-premises, and resources like printers, compute resources and Internet of Things (IoT) actuators. The objective of the paradigm is to prevent unauthorised access to data and resources but at the same time enable authorised and approved subject to have access to the same. The word subject can mean user, device or an application/ service. The paradigm also envisions making the access control enforcement as granular as possible. Thus, “Zero trust architecture (ZTA) is an enterprise’s cybersecurity plan that utilizes zero trust concepts and encompasses component relationships, workflow planning, and access policies. Therefore, a zero-trust enterprise is the network infrastructure (physical and virtual) and operational policies that are in place for an enterprise as a product of a zero trust architecture plan.” Zero trust (ZT) provides a collection of concepts and ideas designed to minimize uncertainty in enforcing accurate, least privilege per-request access decisions in information systems and services in the face of a network viewed as compromised. The crux of the concept is that trust must be continually evaluated. If a subject needs access to data or resources, it is granted after authentication and authorisation, but it will not go beyond the minimum privileges needed to perform the mission.

Benefits of Implementing ZTA

The ZTA paradigm comes packed with a slew of benefits:

1. Supporting employees/ workers with secure and reliable access to a multitude of resources from anywhere using any device, any time
2. Resource protection irrespective of whether it is on-prem or cloud
3. Improving visibility and governance: who, what, and how users are accessing enterprise data and apps.
4. Limiting of insider threat borne of the need-to-know approach to resource access
5. Limiting of lateral movements of attackers in the system which perimeter security-oriented networks are otherwise prone to.
6. Limiting the cost for recovery and mitigation
7. Ensuring confidentiality and security of sensitive enterprise data
8. Enhanced risk mitigation courtesy of continuous assessment and review of resource access

ZTA: How it Works

The Zero Trust Architecture evaluates the level of confidence about the subject’s identity for a unique request and if the device used to place the request have proper security posture. The system also evaluates if there are other factors that should be considered and that change the confidence level. Also the access rules are made as granular as possible to enforce those least privileges needed to perform the action in the request. Image courtesy: https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-207.pdf Three terms assume significance in the context of Zero Trust. They are Implicit Trust Zone, Policy Decision Point (PDP) and Policy Enforcement Point (PEP). Implicit Trust Zone represents an area where all the entities are trusted to at least the level of the last PDP/PEP gateway. In other words, the PDP/ PEP engine decides as to whether a request for resource should be allowed access to the Implicit Trust Zone from where it can access the resource. The PDP/ PEP gate is more like an airport security checkpoint. The passengers, once they have been through the security check are granted access to boarding gates where they can wait for the entry to the airplane. They are considered worthy of trust once they are through. The boarding area is thus the Implicit Trust Zone in the analogy. In our case, the idea is to explicitly authenticate and authorize all subjects, assets and workflows that make up the enterprise.

Challenges of Implementing the ZTA

For where there are opportunities, there are challenges. The road to ZTA implementation has its fair share of challenges.

1. There is no single solution encompassing all the tenets of Zero Trust. A one-size-fits-all approach is off the table for obvious reasons. Many different technologies need to be integrated and often, they are of varying maturity.
2. Investment in terms of time, resources and technical capabilities. Migration of extant and legacy systems to a Zero Trust environment is not as easy as it sounds.
3. And finally, there is no such thing as 100% fool-proof security. The ZTA control plane is still susceptible to compromise.

Overcoming ZTA Implementation Challenges

The challenges need a holistic approach to overcoming them.

1. Getting hold of visibility: The resources within the enterprise and who needs access to the same and when; these queries should be ascertained at a granular level. This exercise must be inclusive of:
   1. Identities
   2. Permissions
   3. Configurations
   4. Activities crisscrossing the cloud infrastructure which are about access to networks and resources that are publicly exposed.
2. Managing risk: Continuous risk assessment exercise across the cloud IT stack including but not limited to:
   1. Identity
   2. Networks
   3. Compute & storage segments
   4. Publicly exposed resources if any
   5. Third-party risks originating from vendors, clients etc.

Taking care of governance: Agencies concerned must implement least-privilege policies by taking care of workflows, continuous integration and delivery pipelines and stave off misconfigurations. Just-in-time access policies are also a must-have rather than awarding engineers with all-access pass for specific, limited-time projects. Tracking behaviour: Anomalies that may be borne out of compromised identities must be detected and mitigated.

Beinex and the Zero Trust Architecture

Beinex has solid experience in fostering Zero Trust Architecture capabilities amongst clients. Considering the fact that 90+ entities of Beinex are government clients, our Digital Transformation Team is well positioned to implement the paradigm in multiple domains. Contact us to know more about our offerings.