Building and testing transforms using Nexla's pre-built transform rules is now even easier with granular control for transform rules

The Nexset Designer and our pre-built transform rules let users easily create transforms that prepare, enrich, and validate data exactly as they need it, without requiring any code. These transforms often contain numerous rules, which can complicate testing new transforms and troubleshooting errors in output data.

We're introducing the ability to granularly disable transform rules in the Nexset Designer to simplify these processes.

🔷  Here's a look at how this feature can help your organization:

• Transform rules can now be disabled, or hidden, individually
  Disabling rules allows users to more efficiently test transforms and identify rules that cause errors or unexpected results in output data.
  
  
  
  
• Disable or re-enable rules with a single click
  Once a rule is disabled, click Run Nexset Rules to apply the remaining rules and preview the output data. Disabled rules can then be modified, deleted, or re-enabled based on the results, avoiding unnecessary rule deletion–recreation cycles.
  
  
  
  
• Disable one or multiple rules
  Any number of transform rules can be disabled—this streamlines testing/troubleshooting processes, no matter how complex the transform is.

Harness the power of GenAI and LLMs to intelligently query your data with Nexla's new RAG flows!

Implementing intelligent data querying through retrieval-augmented generation is now even easier with Nexla's RAG flows. 

RAG data flows provide a simplified way for organizations to harness the information synthesis power of GenAI & LLMs to intelligently query any data, with rapidly generated responses presented in natural, easy-to-understand language. With automatically supplied code, the querying function of RAG flows can also be effortlessly integrated into external applications, such as customer-facing and internal chatbots.

🔹  Query Any Data 
LLMs are trained with vast amounts of data, but organizations often need to query specific data relevant to a specific scenario and/or data that is not exposed for LLM training. With RAG flows, flow owners & administrators designate exactly which information is referenced to formulate query responses—including brand new or internal data. 

🔹  Application Integration
Nexla automatically supplies the complete API configuration cURL needed to integrate RAG-powered querying into external applications—for example, a customer-facing chatbot that provides product recommendations and information. Simply copy the cURL, and insert it into the application's code.  

To learn more about RAG flows and how to create them in Nexla, watch the video below or contact the Nexla support team.

The Nexla UI now includes new NOVA features that make creating new Nexsets even faster and more efficient with GenAI!

With these enhancements, users can harness the power of NOVA - Nexla's  GenAI-based chatbot to easily generate transformed Nexsets and/or transform code using natural-language prompts.

In expanded data flow visualizations, the new Generate option available in the Nexset menu lets users create new transformed Nexsets by simply entering a natural-language prompt. Using NOVA to create new Nexsets in this way avoids the need to manually construct transforms, providing significant time savings and increasing accessibility. 

• Create new Nexsets with NOVA in FlexFlow, DirectFlow, and Spark ELT data flows.
• Prompts can be as general or specific as needed--for example, "Filter the data to include only records with the order_date value 2024-12-20" or "Please remove all records with missing values".
• To ensure that each prompt is interpreted correctly, NOVA provides a description of the Nexset that will be generated and asks for user confirmation.
• Generated Nexsets are tagged with the #NexlaAI marker, making them easy to identify and track.
  
  

🔈 Use NOVA to write custom transform code
In the Nexset Designer, users can also harness the power of NOVA & GenAI to efficiently create custom code-based transforms with the new Generate Code feature. The Generate Code button is available when creating or editing a Transform: Code rule. 

Clicking this button allows users to input a natural-language prompt describing the desired transform, and NOVA will provide a response containing the corresponding transform code within the chat window. Simply click the Use Code button to apply the generated code to the transform rule.

Nexla's latest update makes orchestrating connected and dependent data flows easy & efficient!

Often, data operations include multiple data flows that are connected or dependent upon each other. For example, an aggregation flow may need to be executed after one or more separate inventory flows, or a set of data flows that share resources may require monitoring and triaging together. With Nexla's new Flow Orchestration feature, our users can create, coordinate, and manage complex sequential and/or interconnected workflows with ease.

🔷 Sequential Flows: Execute a data flow upon completion of another data flow
During data flow creation in Nexla, users can directly configure the flow to be executed upon the completion of another data flow, avoiding the need for troublesome chronological scheduling. With this option, after each run of the selected flow, once data movement into the destination is complete, the dependent data flow will be executed. 

For more information about how these features can benefit your organization, see the video below, or contact the Nexla support team.

Nexla's new Private Data Product Marketplace enables easy and effective data sharing & discovery within organizations.

In large organizations and those that work with high volumes of data, ensuring that data is available to & usable by organization members who need it while also adhering to applicable governance requirements can be a challenge. Nexla users can now take advantage of the Private Data Product Marketplace to enable efficient, well-governed collaboration between data producers & consumers.

🔉  Benefits of the Private Data Product Marketplace include:

• Data consumers can discover & access Nexsets via a simple, shopping-like interface. There, users can view a Nexset's schema, status, documentation, rating, and ownership, as well as request access to the Nexset.
• Data producers publish Nexsets to the marketplace, with full control over the Nexset's visibility to other users - a Nexset can be shared with teams, individual users in the organization, the entire organization, or even users in other organizations.
• Marketplace custodians & administrators curate each marketplace to best fit their organization’s needs, ensuring that the included Nexsets are easily discoverable by creating and assigning domains, approving new Nexset listings, delisting Nexsets as needed, and approving or denying Nexset access requests according to governance policies.

To enable the Data Product Marketplace and learn more about how it can benefit your organization, contact the Nexla sales team.  

Introducing the newest data flow types now available in Nexla: DirectFlow, ELT, and BYO

Nexla's data flow types expedite flow creation by providing pre-built, streamlined data flow templates customized for common use cases. In the latest update, we've added 3 more flow types:

• DirectFlow – Designed for high-throughput point-to-point data processing wherein minimizing data processing latency is a critical need
• ELT – Streamlined for ELT workflows to provide seamless movement of unmodified data from APIs into databases and data warehouses
• BYO – Enables highly specialized data processing by allowing users to incorporate custom runtimes that define every aspect of a data flow, providing the flexibility of tailored data processing with all of the operational benefits of the Nexla platform

For more information about these flow types, watch the videos below: 

We're introducing a new way to interact with your organization's data through NOVA—the Nexla GenAI chatbot!

In the new NOVA chatbot interface, users can directly query their organization's data to obtain rapid, thorough, and accurate insights, expediting workflows by consolidating the data analysis process.

🔸  Harness the power of RAG & LLMs
When a query is submitted, NOVA uses retrieval-augmented generation (RAG) to provide comprehensive responses based on the selected data and any available metadata and/or other contextual information. RAG combines the power of search algorithms with the capabilities of large language models (LLMs), producing complete, accurate, and easily understandable responses.

🔸  Setup is easy
Initializing a NOVA session requires a service key, which users can generate via a simple one-step process in the Nexla UI. Once generated, this service key is stored in the user's account and can be reused to initialize all future NOVA sessions.

🔸  Query data from REST APIs, SQL databases, & vector databases
NOVA can be used to directly query detected and transformed Nexsets containing data from REST API sources, SQL databases, and vector databases. 

Learn more about NOVA and how to use it to query your data in our Querying Data Using GenAI tutorial!

Nexla's new API destination testing feature makes API-based data exchanges even easier!

In Nexla, creating data flows that send data to any API-based destination is easy and requires only a few simple steps. However, API destinations often have many strict configuration and payload formatting requirements that must be met in order for incoming data to be successfully received. 

Now, Nexla users can send a sample payload when creating an API-based destination to ensure that data will be successfully received by the destination system.

Click the image below to learn how to use the API testing feature in our step-by-step interactive tutorial!

Benefits Nexla users can enjoy with this new feature include:

✅  Efficient Destination Creation & Troubleshooting

• Test results include the server response received, simplifying the error troubleshooting process by displaying needed information directly within the destination setup screen. 
• Destination testing can be performed iteratively—there is no limit on the number of sample payloads that can be sent.

✅  Rapid Schema Modifications

• Sample payloads are displayed in a fully editable text field, enabling efficient payload format and/or content changes. 
• When a sample payload is modified, users can choose to easily apply some or all of these changes in the Nexset Designer using a schema template generated from the sample payload properties.

Nexla's newest update brings enhanced data flow creation features, along with a streamlined self-signup process for new users.

💡 Data Flow Types
Now, when creating a new data flow, users can select from several pre-built flow-type templates, including FlexFlow, Replication, Spark ETL, and DB-CDC, all listed in the flow type selection screen. 

• FlexFlow: All-in-one flow type that facilitates seamless data movement & supports multiple destinations, data transformations, and both streaming and real-time data flows
• Replication: Designed for rapidly moving unmodified files between storage systems when both speed and file structure retention are critical
• Spark ETL: Customized for transferring and modifying big-data workloads stored in cloud databases or Databricks
• DB-CDC: Uses change data capture (CDC) to replicate tables across databases and/or cloud warehouses

For more information about Nexla's data flow types, watch the video below:

🔹 Self-Signup
With the new self-signup process, anyone can easily sign up for a Nexla trial to experience how the powerful Nexla platform can enhance your data workflow!

To sign up for a trial account, simply click the Sign Up button at the bottom of the login screen, and enter your information.

Create Nexsets using SQL query-based transforms. Generate output data based on complex aggregations across input records.

With the new Transform: Aggregate rule type now available in the Nexset Designer, transform rules that are applied across multiple records in a Nexset can now be created with SQL queries.

Transform: Aggregate rules allow users to easily create and apply transforms that aggregate records according to attribute values directly in Nexla. Typically these operations require storing raw records in a relational database or warehouse where users then run their SQL queries. But with this new capability in Nexla users can save time and money by  performing these SQL queries while the records are in flight.

Record-aggregation transforms can be applied to produce output data for reporting, analytics, notifications, and more. These transforms can be customized for any dataset, workflow, or use case.

Additionally, with branched data flows in Nexla, multiple transforms can be individually applied to a single Nexset, creating parallel streams to deliver both record aggregations and transformed data to downstream destinations in a single flow.

To learn more about record aggregation with SQL transforms in Nexla, see Record Aggregation Transforms (SQL) on Nexla Docs.