Connect Tray to IBM Cognos Analytics: Dashboards in Minutes

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Visualize Tray Data in IBM Cognos Analytics

Kondado enables business teams to visualize Tray data directly in IBM Cognos Analytics without technical complexity or engineering resources. You simply connect your Tray store as a data source, select IBM Cognos Analytics as your destination, and choose which pipelines to replicate from the 14 available options. The platform handles the data movement automatically, delivering fresh information to your dashboards on a configurable schedule you control, whether that is every 5 minutes or once daily.

With this connection, marketing and operations teams can track sales performance, monitor inventory levels, and analyze customer behavior using Cognos Analytics powerful visualization capabilities. No coding knowledge is required: just select your data endpoints and start building insightful reports that drive smarter business decisions for your ecommerce operations.

Kondado connects Tray to IBM Cognos Analytics via a direct integration that requires no intermediate databases or complex setup, allowing you to replicate 14 different pipelines including Orders, Customers, and Products on update frequencies ranging from every 5 minutes to daily.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Combining Tray ecommerce data with IBM Cognos Analytics visualization opens powerful analytical possibilities for growing businesses. By replicating the Orders and Sold Products pipelines, you can create dynamic sales performance dashboards that reveal your best-selling items and peak purchasing periods. The Customers and Discount Coupons pipelines enable you to segment your audience and measure promotional campaign effectiveness directly within Cognos Analytics.

This connection helps operations teams identify inventory trends using the Products and Products (Kits) pipelines while financial staff monitors cash flow through the Payments and Order Invoices data. These combined insights allow you to optimize stock levels, refine marketing strategies, and improve customer retention without manual data exports or spreadsheet juggling.

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Tray data available in IBM Cognos Analytics

available pipelines

328

extractable fields

Available integrations

Integration	Description
Customers	Includes information such as name, email, and registration date, along with modification date and last visit.
Discount Coupons	Contains details such as coupon code, creation date, and discount value, along with usage restrictions.
Newsletters	Presents information about the customer's email, newsletter status, and creation and modification dates.
Payments	Includes data on payment methods, status, and values of transactions made by customers.
Orders	Provides information such as order ID, order date, and delivery status, along with customer details.
Order Details	Includes detailed information such as order ID, billing address, and additional cart values.
Order Details: Mercado Livre	Presents data such as customer ID, estimated delivery date, and information about the purchased product.
Additional Product Information for Orders	Contains additional information such as product ID and product name related to each order.
Order Invoices	Includes data such as invoice ID and product CFOP, essential for accounting.
Order Transactions	Provides information on transaction status and values associated with each order made.
Products	Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.
Products (Kits)	Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.
Sold Products	Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.
Products: Variants	Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

Customers

Includes information such as name, email, and registration date, along with modification date and last visit.

Discount Coupons

Contains details such as coupon code, creation date, and discount value, along with usage restrictions.

Newsletters

Presents information about the customer's email, newsletter status, and creation and modification dates.

Payments

Includes data on payment methods, status, and values of transactions made by customers.

Orders

Provides information such as order ID, order date, and delivery status, along with customer details.

Order Details

Includes detailed information such as order ID, billing address, and additional cart values.

Order Details: Mercado Livre

Presents data such as customer ID, estimated delivery date, and information about the purchased product.

Additional Product Information for Orders

Contains additional information such as product ID and product name related to each order.

Order Invoices

Includes data such as invoice ID and product CFOP, essential for accounting.

Order Transactions

Provides information on transaction status and values associated with each order made.

Products

Table contains information about products, including id, name, and variants. Fields such as attributes_id and attributes_value provide additional details.

Products (Kits)

Table presents product kits, detailing id and attributes. Fields such as attributes_customer_attribute_id provide information about the characteristics of the kits.

Sold Products

Table displays sold products, including id and sales information. Fields such as order_id and order_item_quantity help understand sales performance.

Products: Variants

Table details product variants, including id and attributes. Fields such as additionalproductinfo_product_id and additionalproductinfo_variant_id provide specific information about each variant.

See all available data →

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Frequently Asked Questions (FAQ)

Answers about visualizing Tray data in IBM Cognos Analytics automatically

How do I set up the Tray connection to IBM Cognos Analytics using Kondado? ▼

Start by adding Tray as a new data source in your Kondado account using your store credentials. Then select IBM Cognos Analytics as the destination and choose which of the 14 available pipelines you want to replicate. The initial data load typically completes within minutes, after which your selected information becomes available for visualization in Cognos Analytics.

What type of dashboards can I build with Tray data in IBM Cognos Analytics? ▼

You can build comprehensive ecommerce dashboards tracking sales trends, customer segmentation, and inventory management using the Orders, Customers, and Products pipelines. Create visual reports that monitor discount campaign performance through the Discount Coupons pipeline or analyze payment method preferences using the Payments data. These custom visualizations help you identify growth opportunities and operational bottlenecks across your online store.

How often does the Tray data update in my Cognos Analytics reports? ▼

You control the refresh schedule based on your business needs, with options ranging from every 5 minutes to daily updates. This configurable schedule ensures your reports reflect recent transactions and inventory changes without manual intervention. You can adjust the frequency anytime as your reporting requirements evolve.

Which KPIs should I track when visualizing Tray ecommerce data? ▼

Focus on metrics like conversion rates using Orders and Customers pipelines, average order value from Order Details, and inventory turnover via Products and Sold Products data. Track campaign ROI by combining Discount Coupons usage with revenue figures from Order Transactions. These indicators help you optimize pricing strategies and stock management decisions.

Can I share my Tray Cognos Analytics dashboards with my team? ▼

Yes, once you build reports in IBM Cognos Analytics, you can distribute them to stakeholders across your organization using the platform native sharing features. Team members can view dashboards even if they do not have Kondado access, since the data lives in your Cognos environment. This simplifies collaboration between marketing, sales, and operations departments.

Do I need technical skills to connect Tray to IBM Cognos Analytics? ▼

No coding or engineering expertise is required to establish this connection through Kondado. The interface guides you through selecting your data source and destination with simple point-and-click configuration. Business users can set up and manage the replication independently without involving IT departments or writing API queries.

What happens if I add new products to my Tray store? ▼

New products appear automatically in your Products pipeline during the next scheduled update, ensuring your Cognos Analytics inventory reports stay current. The Additional Product Information for Orders pipeline also captures new item details as they enter your order workflow. You do not need to manually reconfigure the connection when your product catalog expands.

Can I send Tray data to other visualization tools besides IBM Cognos Analytics? ▼

Yes, Kondado allows you to replicate your Tray data to multiple destinations simultaneously, including Power BI, Looker Studio, or Google Sheets. You can also choose BigQuery or PostgreSQL for advanced analytics needs. This flexibility lets different teams access the same Tray data in their preferred business intelligence platforms.

Try out all the features for free for 14 days

Get started for free

Get started for free

Get started for free

Connect Tray to IBM Cognos Analytics: Dashboards in Minutes

Get started for free

Visualize Tray Data in IBM Cognos Analytics

Tray data available in IBM Cognos Analytics

Available integrations

How to create Tray dashboards in IBM Cognos Analytics

Connect Tray Store to Kondado

Choose IBM Cognos Analytics

Configure Refresh and Visualize

Access Tray data in IBM Cognos Analytics and combine it with dozens of other data sources

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