ATPCO seamlessly integrates self-service knowledge entry capabilities into its system, leveraging Amazon DataZone’s power to accelerate innovation. By empowering users to easily contribute and update information, the platform fosters a collaborative environment where data-driven insights can be shared rapidly across teams. This streamlined approach enables ATPCO to drive faster decision-making, optimize processes, and ultimately, enhance customer experiences.

In today’s data-driven environment, companies across various sectors recognize the profound value of information in informing decisions, fostering innovation, and developing new products that cater to customer needs. Despite this, numerous organizations continue to struggle with empowering their employees to effectively locate, access, and utilize information while maintaining robust governance controls. Numerous limitations hindering the analytics journey prevent swift innovation and timely decision-making.

Does the evolving landscape of airline retailing enable carriers and third-party platforms to offer passengers the most compelling fares at the optimal moment? ATPCO’s achievement is truly remarkable, boasting an unparalleled level of fare knowledge that encompasses over 89 percent of the world’s flight schedules. The corporation collaborates with more than 440 airlines and 132 channels, overseeing and processing over 350 million fares within its vast database at any moment. As the leading travel technology company, ATPCO aims to revolutionize airline retailing through cutting-edge innovation, while fostering unwavering trust within the airline community as a valued partner. ATPCO strives to enable data-driven decision-making by providing easy access to high-quality insights that are transparently governed across all business units, empowering informed choices.

We illustrate ATPCO’s value proposition through a compelling use case, demonstrating how the company leverages AWS services, including [insert specific service], to empower data discovery across diverse business models, thereby enabling rapid innovation for customers. To enhance your understanding, we suggest starting by familiarizing yourself with the terminology employed within this article.

Use case

ATPCO’s use cases include assisting airlines to gain insight into the products, including fares and ancillaries such as premium seat selection, that are being offered and sold across various channels and customer segments. To inform this goal, ATPCO aims to leverage three distinct knowledge sources and derive actionable insights on product efficiency.

• ATPCO’s data powerhouse processes over 1 billion airline ticket gross sales transactions.
• – Nearly 9 out of every 10 airlines globally rely on ATPCO’s pricing expertise. ATPCO is a leading provider of pricing and merchandising solutions that empower airlines, global distribution systems (GDSs), online travel agencies (OTAs), and other sales channels to present customers with clear visual comparisons of various offers.
•  AtPTCO buyers gain access to anonymized data for in-depth analysis and regulatory adherence.

To extract valuable insights that can be disseminated as a knowledge product for airways, an ATPCO analyst requires access to relevant information entities, enabling them to uncover the most pertinent knowledge related to this topic, then utilize it in a SQL client like to form hypotheses and establish connections.

Prior to the introduction of Amazon DataZone, ATPCO’s analysts had to rely on informal conversations with colleagues to identify potential knowledge assets, lacking a straightforward means to uncover such assets across the organization? The delay in their innovative pace was directly attributed to the increased duration required for their analytics expedition.

Answer

To tackle the challenge, ATPCO drew inspiration from the modern architecture of a knowledge graph. A knowledge mesh framework supplants traditional centralized platforms with a decentralized warehouse or lake, acting as a clearinghouse for corporate knowledge. This model empowers distributed ownership of information among creators, who publish and curate their knowledge products, making them searchable, accessible, and usable by consumers.

Amazon DataZone enables high-performance collaboration by empowering teams to share ownership of responsibilities, thereby allowing them to operate more like co-creators rather than gatekeepers. In Amazon DataZone, knowledge house owners can publish their knowledge and its associated metadata catalogue to the ATPCO DataZone domain. Customers seeking related information can easily find relevant content using these user-friendly metadata tags. Knowledge shoppers seeking entries on ATPCO’s knowledge platform now submit their requests directly to the content writer or designated reviewer for evaluation and approval. When customers utilize the provided information, they execute this task within their unique AWS accounts, assigning the corresponding consumption costs to their individual pricing tier rather than a centralized pool. Amazon DataZone eliminates redundant knowledge storage, thereby minimizing costs and simplifying compliance oversight. Amazon DataZone streamlines operations, leveraging a suite of familiar AWS services – including, for instance, and – in a transparent manner fully auditable by customers.

The diagram provides an outline of the solution using Amazon DataZone and various AWS services, following a completely distributed AWS account model. In this setup, data sets like airline ticket sales, ticket pricing, and de-identified customer data are stored across multiple member accounts in AWS.

Implementation

Let’s explore how ATPCO addressed the challenges faced by analysts in accessing and utilizing data quickly to support their airline clients efficiently.

The four key components of this design:

1. Streamline account governance and identity administration processes to ensure seamless access control and optimal resource utilization.
2. Can you create a secure, governed, and organized Amazon S3 data lake by configuring an Amazon DataZone?
3. Publish knowledge belongings.
4. Consume knowledge assets to facilitate the discovery of meaningful insights through analytical examination.

Governance of Accounts and Identity Administration must align to ensure seamless interactions within the organization. This requires establishing clear policies, procedures, and roles for managing user identities and access permissions. Effective governance ensures accountability, transparency, and compliance with regulatory requirements, thereby safeguarding organizational assets. By streamlining account management and identity administration, the organization can mitigate risks associated with unauthorized access, data breaches, or insider threats.

Before commencing, inspect your existing cloud configuration, including data architecture, to ensure alignment with ATPCO’s parameters. To streamline this setup, we’ve distilled it down to its core components for the purpose of this blog post.

1. ATPCO leverages the services of a dedicated provider to establish and manage its AWS account infrastructure.
2. ATPCO organizes its current knowledge lake sources into distinct accounts, each belonging to separate data-generating entities. Having distinct accounts enables efficient management entry, reduces the impact of potential errors, and facilitates allocation and management of costs and resource utilization effectively.
3. ATPCO’s standardized knowledge lake architecture is comprised of a single repository for knowledge storage, a crawler and catalog system for seamless updating and technical metadata storage, and, in hybrid entry mode, a mechanism for governing knowledge entry permissions.
4. ATPCO established two novel AWS accounts: one dedicated to personalizing the Amazon DataZone environment, and another for a shopper workforce to leverage for analytics purposes.
5. ATPCO successfully enabled and integrated its identity provider (IdP) for streamlined authentication purposes.

Assuming identical setups allows for similar choices, tailored to individual needs and preferences.

What are the key characteristics of a well-configured Amazon DataZone? Can you provide more context about this setup process? Which specific steps do you suggest to create and configure an Amazon DataZone area?

Once your cloud settings are prepared, the subsequent steps in Part Two will guide you through creating and configuring a secure Amazon DataZone environment. The platform enables organizations to efficiently manage their collective knowledge, connecting individuals and fostering collaboration through a dedicated enterprise knowledge catalogue and intuitive online portal. This seamless sharing and utilization experience empowers both publishers and end-users to leverage knowledge assets in real-time. ATPCO’s knowledge platform workforce successfully set up and customized their designated workspace.

: Area administrator

Visit your local area account online. When utilizing Company Workforce IDs for authentication, select the appropriate AWS Region where your Identity Center instance is deployed. Select .

1. Enter a and .
2. Depart cleared
3. Depart from the default selection. AWS establishes an IAM role in your account on your behalf, granting the necessary IAM permissions to access Amazon DataZone APIs.
4. Given the scope doesn’t align with our area of expertise, we won’t consider publishing or incorporating this information into our account.
5. Skip for now. You may always return at a later time to edit this section and add relevant tags.
6. Select .

Upon completing the site development process, you’ll encounter a Site Element Web Page that bears resemblance to the following. Is the Identity and Access Management (IAM) Identification Heart feature initially set to an inactive state?

: Area administrator

By default, access to your Amazon region, its associated APIs, and the unique internet portal is granted to IAM principals within this AWS account, provided they possess the required IAM permissions. To enable ATPCO’s employees to seamlessly utilize Amazon DataZone while leveraging their existing company-issued single sign-on (SSO) credentials, without requiring an additional secondary federation to IAM roles. AWS Identity and Access Management (IAM) provides a centralized service to manage access and permissions across AWS resources. You may skip this step if you plan to use IAM principals immediately for accessing Amazon Data Zone.

Go to your Amazon DataZone dashboard and click on the “Elements” tab.

• Scroll right down to the part and choose . When options appear beneath me. Because activation requires explicit permission, customers and teams must be added to access your designated space. Select

Let’s introduce a gaggle of birds to the area, providing its members with seamless access and unhindered mobility. In the section of our website dedicated to the local environment, locate the bottom-most portion of the page and click on the designated tab. Please select an option from the dropdown menu.

1. Identify the main letters within a group and select them from the available options. Once you’ve designated the targeted groups,
2. The teams are successfully added on the area’s element webpage by selecting the tab, followed by choosing from the dropdown options.

Area Administrators and AWS Account Owners

Amazon DataZone streamlines the setup of distributed AWS accounts by isolating data ownership from data consumption, akin to Amazon Athena’s usage. Data assets reside in separate accounts, each owned by its corresponding data owner. We name these . Amazon DataZone orchestrates secure cross-account knowledge sharing among its counterpart AWS companies. To successfully integrate an area and account, homeowners must complete a one-time process: they must share the area with their account and configure the latter to work seamlessly with Amazon DataZone. For ATPCO, four desired related accounts exist: three containing knowledge assets stored in Amazon S3 and cataloged in AWS Glue – airline ticketing knowledge, pricing knowledge, and de-identified buyer knowledge – and a fourth account dedicated to analysts’ consumption.

Associating an account primarily involves sharing the Amazon DataZone area with designated accounts, leveraging AWS RAM to establish a secure resource coverage. ATPCO’s knowledge platform is managed by its dedicated workforce members, who carry out these tasks.

1. Within the Amazon DataZone console, users must first sign up for an Area account, then navigate to the designated Area Element webpage, followed by a downward scroll to locate and select the relevant “tab” option. Select .
2. Enter the AWS Account ID of the primary account to be linked.
3. Consolidate all accounts by adding one additional relationship and iteratively repeating this process for each remaining account. Four to-be-related accounts exist for ATPCO.
4. When full, select Request Affiliation.

Upon completing account registration, the account owner must subsequently configure their account for utilization with Amazon DataZone. The primary implication of this consent is that the account holder grants Amazon DataZone permission to perform actions within the account, including granting access to Amazon DataZone initiatives following a successful subscription request authorization.

1. Sign up for the relevant account and navigate to the Amazon DataZone console within the same region. Click on the “Select” button.
2. Amazon DataZone: Unlocking Your Data’s Potential

3. Which Amazon DataZone blueprint do I need to enable? As a result of ATPCO’s use case, we leveraged the capabilities of Amazon S3 for data storage and utilized Amazon Athena for querying and analysis purposes.

4. Upon approval of a subscription request in Amazon DataZone, the platform enables Amazon DataZone to leverage IAM and LakeFormation to manage IAM roles and permissions for data lake sources seamlessly. Amazon’s DataZone feature allows creation of S3 buckets and AWS Glue databases and tables within your account, concurrent with empowering customers to establish Amazon DataZone initiatives and environments upon enabling this functionality. In Amazon DataZone, this setting determines the S3 bucket used to store data on behalf of customers who utilize your account for data warehousing purposes.

5. Select . Clicking on this link takes you directly to the Related Domains Desk for the specified account, where a detailed list of associated domains is displayed. The social media landscape demands we expand our brand’s digital footprint by creating multiple accounts that are interconnected yet distinct in their messaging and tone.

Once associations are configured by accounts, you’ll notice the standing mirrored reflected in the tab of the area element webpage.

: Area administrator

To fully leverage the organized space, a crucial next move is enabling seamless access for Amazon DataZone area clients through relevant AWS accounts. You create a setting profile, which aids non-technical users in effortlessly launching their publishing or knowledge consumption endeavors.

The template features pre-defined technical specifications, including blueprints, AWS account IDs, and specific areas. ATPCO’s knowledge platform enables its workforce to create a customized setting profile for each relevant account.

To access the Amazon DataZone console, platform workforce members must first sign up for an area account and navigate to the area element webpage, then select “Go to” in the upper right corner to access the web-based Amazon DataZone portal?

1. Click on the DataZone icon and select the option that appears. What are some of the key responsibilities that fall under the purview of an area administration, considering their role in overseeing multiple departments? You will be redirected to your newly created project’s webpage.
2. On the undertaking webpage, click the designated tab and subsequently choose the option from the navigation pane. Choose .
   1. Reputation Score:
   2. As owner of the venture, I will utilize the blueprint.

   3. Identify the AWS account that leverages extensive sales expertise, pairing this strength with well-known areas such as AWS Glue and Amazon Athena consumption for fresh data sources.

   4. Depart and
   5. Cannot be improved

Reconcile all outstanding transactions across each account to ensure accurate financial reporting and compliance with regulatory requirements. With Amazon DataZone, customers can establish tailored environments for their projects, leveraging specific AWS resources within designated accounts for publishing and consumption purposes.

Half 3: Publish belongings

As Half 2 reaches completion, the platform is primed for publishers to register and start uploading primary content assets to the corporate knowledge repository, allowing prospective knowledge consumers to find relevant materials that aid their analysis endeavors? ATPCO unveiled its inaugural knowledge asset designed for internal assessment, specifically gross sales data from its airline partners. ATPCO had previously extracted, remodelled, and loaded the data into a staged Amazon S3 bucket, which was then catalogued using AWS Glue.

: Knowledge writer

Amazon’s DataZone enables multiple stakeholders to collaborate seamlessly on data-driven insights and knowledge sharing. In this ATPCO use case, the initiative aims to leverage published sales data as a valuable asset within the organization. By anchoring the ultimate knowledge asset to an enterprise, rather than an individual, it can endure as a valuable resource beyond the tenure of any single employee or team.

1. Accessing the URL provided by our area administrator, I will navigate to the designated knowledge portal’s sign-in webpage. Upon arrival, I will utilize either Integrated Amazon Management (IAM) or Single Sign-On (SSO) authentication protocols to securely log in and ensure seamless access to the portal’s knowledge repository. Upon signing into the information portal, choose “Enter” a reputation similar to Gross Sales Knowledge Property and opt for.
2. To invite additional team members to collaborate on the project, simply click. On the webpage, identify relevant IAM or SSO principals, then assign a specific task to each one within the project scope. Have unlimited permissions within the project, precluding any ability to modify or terminate the initiative or management roles. Complete your membership modifications now.

: Knowledge writer

Programs often consist of diverse settings. Amazon DataZone environments comprise curated collections of configured data sources, including S3 buckets, AWS Glue databases, and Athena workgroups. When developing data products that require multiple stages of processing, such as raw, filtered, processed, and curated data, these tools can be invaluable in managing each phase efficiently using separate AWS resources.

1. Upon logging into the information portal and initiating the task, click on the designated tab and then select the desired option.

   Processed: Knowledge refinement and validation have been achieved through rigorous analysis, ensuring accuracy and consistency in understanding the concept of processed food products.

2. Select the setting profile the area administrator created in Half.
3. Select . I’ve realized I’m no longer interested in delving into the nitty-gritty details of my Amazon Web Services (AWS) account settings. The setup process for Amazon DataZone’s Lake Formation, Glue, and Athena is expected to take several minutes.

: Knowledge writer

ATPCO has leveraged AWS Glue to catalogue its wealth of knowledge. Amazon DataZone can leverage AWS Glue as a knowledge source. Amazon DataZone knowledge supply for AWS Glue showcases a collection of AWS Glue databases, allowing users to establish table-level schema standards based on database name. As AWS Glue crawlers continually scan for fresh knowledge and metadata, you can execute an Amazon DataZone ingestion job against an Amazon DataZone data source (AWS Glue again) to extract all matching tables and technical metadata – essentially serving as the foundation for various data assets. A data ingestion job can be executed either manually or automatically according to a predetermined schedule.

1. Upon logging into the information portal and launching the project, click on the designated tab, followed by selecting the relevant option. Users must initially select the specific column they wish to use for their reputation on the knowledge supply. To achieve this, users can navigate to the “Knowledge Supply” tab within their Glue interface. Next, they should click the “Select” button situated beside the “Reputation” heading. This will prompt a drop-down menu where users must enter a reputation type that aligns with their specific Processed Gross sales data requirement, specifically choosing the “as the sort” option.
2. Selecting the Processed setting in Step 3.2 allows you to streamline your data processing workflow. Within the field, select a worthy option or choose from the instructed AWS Glue databases that Amazon DataZone has recognized within your AWS account. You could potentially add additional standards and another AWS Glue database.
3. For , choose . This allows for the assessment and enrichment of instructional assets before publishing them to the business knowledge repository.
4. Hold this field as chosen. Amazon DataZone provides streamlined enterprise naming conventions for information assets and technical schemas, making it easier for customers to discover and access published assets.

5. By arranging your AWS Glue knowledge in a clear and organized manner. Select .

6. For , choose to . You may be able to return at a later time to automatically rerun this data processing task according to a predetermined schedule. Select .
7. The following options were evaluated: Option A, Option B, Option C, and Option D.

To initiate the ingestion job for the first time, click on the top-right corner. This can begin the job. The runtime depends on the complexity of your knowledge graph, encompassing factors such as the number of databases, tables, and columns involved. Refresh your standing by choosing.

: Knowledge writer

After the ingestion job is complete, the corresponding AWS Glue tables are automatically added to the organization’s catalog. You can then assess the asset alongside automated metadata generated by Amazon DataZone, append additional metadata as needed, and publish the asset seamlessly.

• Upon signing into the information portal, navigate to the designated section and select the desired option. You can assess each piece of metadata generated by the ingestion job. What are we looking to achieve as our ultimate outcome? On the asset element webpage, you can modify the asset’s name and description to facilitate easier discovery, especially within a list of search results.
• **Immersive Experience**
  You may want to consider editing this section to provide a more vivid description of the asset, utilizing markdown formatting to enhance the visual appeal.

  Let me know if you’d like me to make any changes! By providing clear and concise information upfront, this can significantly reduce the number of inquiries from customers seeking further clarification on their requests.

• You can potentially edit the technical schema (columns), including adding company names and detailed descriptions. When you enable automated metadata technology, you will then see suggested metadata options here that you can either accept or decline.
• Once enriched, the asset can be made searchable within the enterprise knowledge catalog for selection.

Assets must provide detailed descriptions of their functions and capabilities? As a result, two additional entities, alongside ATPCO, took the initiative to integrate pricing and de-identified buyer insights into their data catalogs.

What do I own that could help me better understand this concept?

With the enterprise knowledge catalog now featuring three distinct revealed knowledge domains, clients seeking information can seamlessly access and initiate their investigation.

In this final stage, an ATPCO knowledge analyst can access the desired data, gain authorized entry, and analyze the information in Athena, laying the groundwork for a knowledge product that ATPCO can subsequently make available to its clients, akin to airlines.

: Knowledge shopper

Upon receiving the URL from my area administrator, I access the designated knowledge portal by navigating to its sign-in webpage and authenticating using either Integrated Authority Management (IAM) or Single Sign-On (SSO) credentials. Accessing relevant information within our comprehensive knowledge repository, we locate suitable assets to facilitate informed decision-making and drive successful evaluations. Within the ATPCO instance, the analyst started by developing a thorough understanding of ticketing concepts. The revenue generated from this event came in the form of gross sales, encompassing ticket sales and additional income streams such as premium seating options.

The information shopper assesses the website’s product page, including its outline and human-readable language in the schema, verifying its utility for the evaluation. They then select . When submitting a subscription request, the info shopper selects a project type, following the same guidelines as creating a project in Step 3.1, and names it “Product Evaluation Project”. The task is to improve the original text in a different style as a professional editor, returning only the revised text without any explanations or comments. Send the request directly to the information writer?

Evaluate each desired knowledge asset for consistency across all four steps: assess the quality, reliability, relevance, and sufficiency of each piece of information. Within the ATPCO use case, this entailed seeking out and subscribing to relevant information.

With the subscription requests poised for authorization, the information shopper configures an Amazon DataZone setup within the project, mirroring Step 3.2’s instructions. The info shopper sets their preferred settings profile for their AWS account and corresponding information lake blueprint.

: Knowledge writer

When a member logs into the Amazon DataZone knowledge portal for the subsequent time, they will be notified about their pending subscription request. Navigate within the Amazon DataZone knowledge portal to access the undertaking. Open the selected tab and then navigate to another one to fulfill the inquiry. What is the intended evaluation framework or methodology being referred to in this inquiry?

: Knowledge shopper

Once the information shopper has successfully subscribed to each of the desired assets by following steps 4.1 and 4.2, they proceed to access the project in the Amazon DataZone knowledge portal. The information shopper can confirm that the undertaking has knowledge asset subscriptions by clicking on the corresponding tab.

Following successful setup of the project with the information lake blueprint enabled in the customer’s AWS account, the data consumer will observe an icon situated in the right-hand panel labeled ” Lake”. Upon selecting this icon, users are seamlessly redirected to the Amazon Athena dashboard.

In the Amazon Athena console, customers viewing their DataZone subscription details are presented with information about the datasets and data sources belonging to their project. Subscribers utilize the Amazon Athena query editor to interrogate their acquired expertise.

Conclusion

In this publication, we demonstrated an ATPCO use case, showcasing how Amazon DataZone enables users across an organization to easily discover relevant data assets using business terminology. Customers can now rapidly access knowledge and create products and insights sooner. By providing self-service access to knowledge with robust governance controls, Amazon DataZone enables organizations to unlock the full potential of their data assets and drive innovation through data-driven decision-making. If you’re seeking a way to fully harness your data and democratize it across your organization, then Amazon DataZone can help transform your business by making data-driven insights more accessible and productive.

For more information on Amazon DataZone and how to get started, refer to the documentation at. Explore the latest demos of Amazon DataZone to discover its cutting-edge capabilities and learn how you can unlock the full potential of your data with this innovative solution.

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In regards to the Creator

Serving as a Senior Technical Product Supervisor for Amazon DataZone, I drive innovative solutions. With over 15 years of expertise in data science and product development, his career has centered on empowering clients to leverage knowledge insights for informed decision-making. Outside his work as a labourer, he revels in discovering fresh and thrilling pastimes, the latest of which is the exhilarating experience of paragliding through the skies.

Serves as the Principal Options Architect at Amazon Web Services (AWS). His passion enables clients to leverage the power of analytics, machine learning, and AI to propel business growth seamlessly. He collaborates with clients to design innovative solutions leveraging Amazon Web Services (AWS).

Serving as Director of Knowledge Engineering at ATPCO, he spearheads the development of cutting-edge cloud-based knowledge platforms. His contributions enable robust, growth-oriented solutions that support the airline industry’s transformative objectives. Through the strategic application of machine learning and artificial intelligence, Raj spearheads a culture of innovation at ATPCO, firmly establishing the organization at the cutting edge of technological advancements.

As a seasoned Senior Options Architect at AWS, boasting over two decades of experience in crafting and scaling complex programs, predominantly within the financial industry, With a strong background in Generative AI, she excels at spearheading software modernization initiatives that harness the power of microservices and serverless architectures to fuel innovation and efficiency.