How Alghanim standardized collaborative workflow creation by implementing the “Alteryx Sandbox Server” platform on AWS that paved the way for 20% better business predictions

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.

Let’s introduce one such tool.

Beinex has a set of tools to automate the migration testing process, and the devices can also process syntax changes between the legacy database and Snowflake. Well, Syntax Migrator is one tool developed by our experts that follows a structured methodology that helps minimise migration risks. It is an error-free, timesaving, automated migratory tool that converts SQL syntax into Snowflake queries.

How does it work?

With the help of a user-friendly tool like Syntax Migrator, we can quickly convert SQL syntax into Snowflake queries by entering the SQL syntax in the console and then pressing the convert button. It is handy, and even persons with no technical expertise can easily use it.

Syntax Migration Platform can aid in:

1. Automatically translating DDL and DML
2. Selection of best possible data type
3. Intelligent usage of Temp and Transient Tables

Automatically translate DDL and DML.

• Creation of different tables views, and procedures can be quickly changed into Snowflake-compatible queries without any help from Snowflake syntax.
• No matter how the complex procedure is, it converts the syntax to Snowflake and maintains the logic and structure of the procedure.

Selection of the best possible data type

1. Syntax migrator selects the best data type available in Snowflake concerning the source data source even if the datatype is disparate.
2. No need to worry about any mismatch in the data while converting to the compatible datatype. All the data properties will be preserved during conversion.

Intelligent usage of Temp and Transient Tables:

Query logic and syntax will be preserved in the migration, which results in the expected results same as of the source system

About Snowflake

The cloud data platform from Snowflake enables a variety of data workloads, including data warehousing and data lakes, as well as data engineering, data science, and data application development across numerous cloud providers and geographies from any location inside the company.

Due to Snowflake's distinctive architecture, almost any concurrent user in the Data Cloud can benefit from near-infinite storage and real-time processing.

The Many Benefits of Migrating to Snowflake Data Cloud

Even though migrating from an on-premises solution to a cloud can be a tedious process, with Snowflake Data Cloud, it is not laborious, and it can reap benefits like the following:

1. Infinite elasticity
2. Highly concurrent
3. Exponential cost saving
4. Superior data security
5. Modern data cloud platform with your data
6. Reduced maintenance overhead
7. Continue to use on-premises transactional platforms
8. Move to pay for what you use instead of heavy AMCs
9. Conversion of queries into a best Snowflake-compatible format

Our Top Cloud Engineering Services Include:

• Cloud Consulting • Cloud Security • Cloud Migration & Modernization and more Feel Free to Schedule a Call: https://beinex.com/cloud-engineering

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About Beinex Cloud Services

By partnering with Beinex, a leading cloud engineering and enablement partner in the Middle East, you can leverage our expertise to optimize your cloud infrastructure, enhance performance, and ensure security and compliance. Our technical prowess allows us to design and implement tailored cloud solutions that align with your business needs, enabling you to maximize the benefits of cloud technology and drive innovation.

Partnering with industry-leading cloud technology providers like Google Cloud Platform, AWS, and Microsoft Azure to build scalable, secure, cost-effective solutions and deliver transformative cloud technology solutions. Beinex has also forged strong partnerships with Snowflake, Tableau, Alteryx, Alation, and Databricks. These collaborations enable us to offer comprehensive solutions that leverage the best-in-class capabilities of these platforms. We can provide our clients with cutting-edge technologies and expert guidance by working closely with our partners.

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How User Roles and Permissions Facilitate Implementing Data Governance

The Alteryx Server helps enterprises implement effective data governance by ensuring every user operation is based on pre-defined user roles and permissions. It optimizes processes and access control and ensures data integrity. User Roles Defining user roles helps businesses ensure a safe and efficient analytics setting that aligns with best data governance practices. Each role assigned to users ensures they have the right level of access to perform their tasks. • Curator /Server Admin: Accessing the admin interface to run administrative tasks- crucial in enforcing governance policies. • Artisan: Publishing, running, and sharing workflows in their private studio and shared collections- ensures control over their workspace. • Member: Running workflows that are shared with them via collections – supports collaboration without giving excess control while adhering to data regulations. • Viewer: Running public workflows on the Server UI home page and in districts – ensures workflow integrity by limiting them to consumption roles. • No Access: No access to all Server assets- ensures data security for confidential data. User Permissions Besides user roles, you can set user permissions to decide what users can do in the Server UI. User permissions are paramount to upholding robust data governance and ensuring that users can only perform tasks within their scope of responsibility. • Scheduling workflows to run at a planned time – ensures timely task completion without manual intervention. • Prioritizing jobs to run those with the highest priority first- facilitates effective resource allocation and alignment with requirements. • Tag a specific worker to run a workflow- ensures resources are allocated right. • Create new collections within a defined structure- supports collaboration without risking data privacy. • Granting server API access to users- enables task automation without compromising governance • Allowing users to create or edit DCM assets- controls access to shared credentials and connections. • Sharing DCM Connection Credentials to run on the server- ensures data security, which is crucial for governance. • Sharing DCM Connection Credentials for collaboration- strengthens data governance by securely handling confidential and sensitive data. • Managing generic vaults- enables secure handling of credentials and sensitive data. • Blocking the user from accessing the Server UI- ensures that only authorized individuals can interact with sensitive data.

How to ensure Effective Data Governance?

For organizations to cater to their specific requirements, implementing and maintaining an effective data governance process is required, which is briefed below:  • Identifying the data assets of your organization. • Classifying your data based on significance and prioritizing data governance actions • Ensuring accuracy, completeness, and consistency of your data for efficient data quality management. • Safeguarding data from unauthorized access • Controlling data access, including giving and withdrawing access to data • Managing your organizational data throughout its lifecycle

Data Governance in Alteryx: Best Practices

The blog gives you a walkthrough of the best practices about how Alteryx handles data governance by ensuring data management and quality.

1. Authenticating and Authorizing Data: The initial aspect to address in data governance strategies is how data is accessed. Alteryx supports the existing safety measures implemented at the database level; it utilizes your username and password when connecting to your data. These credentials authenticate users and ensure they can only access the data permitted. Alteryx also supports pass-through authentication, facilitating access to data using network identity and authenticating users with the same credentials they use for access. It eliminates the need to manage separate usernames or passwords within Alteryx. In short, Alteryx easily integrates with your organization's existing security infrastructure, leveraging authentication mechanisms to ensure secure data access. 2. Managing Data Effectively: A standout factor in Alteryx's data management is that it does not require the creation of a distinct persistence layer for data storage during processing. The Alteryx server is designed to support multi-tenancy, using in-memory processing and handling temporary data in a sandboxed setting. This means that a single instance of an Alteryx Server can manage multiple workflows simultaneously. Different departments can use the same platform without the risk of unauthorized data access between them. 3. Tracking Data Lineage The drag-and-drop interface of Alteryx offers robust visualizations of the transformations occurring within the workflow. Organizations get a detailed knowledge of the data sources, how they are collected, prepared, blended, and analyzed, the workflows being run, and the count of records read and written. 4. Defining Data Ownership and Stewardship Establishing clear data ownership and stewardship and assigning responsibilities for data sets and workflows is important, especially in an environment like Alteryx where multiple users engage with data. Data ownership is about taking responsibility for the accuracy, privacy, and availability of a data set. Data Stewardship ensures data integrity and quality by implementing policies and ensuring proper documentation. Defining these roles clearly within the organization fosters accountability and reduces data misuse risk. 5. Leveraging Metadata and Data Cataloging Metadata is integral to comprehending your data's context and lineage. The Alteryx Connect tool helps handle metadata and build a centralized data catalog. Data catalogs allow users to discover available data easily, track where the data comes from, and enhance collaboration by sharing and reusing datasets and workflows. 6. Ensuring Data Security and Access Controls When using Alteryx, enforcing appropriate security measures ensures that only authorized users can access sensitive data. To minimize the risk of a data breach, Alteryx helps organizations by providing robust user access control options, supporting encryption of sensitive data, and establishing validating processes for workflows. 7. Monitoring Data Quality Data quality is paramount to effective data governance. Alteryx streamlines and automates data quality monitoring by: • Providing data profiling and validation tools to check for duplicates, inconsistencies, and missing values. • Utilizing Alteryx Server to schedule periodic audits, maintaining data integrity over time. • Setting up alerts or automated reports to notify data owners or stewards of any data quality issues that arise. Data governance is beyond data management. It extends to the policies and processes that decide how an organization should use data while aligning with its goals. With effective data governance, businesses can boost data accuracy and security, enhance efficiency, and boost business value by complying with regulations, tracking data quality, and eliminating discrepancies. With Alteryx's built-in capabilities and powerful tools, organizations can manage the multidimensional challenges of data governance.