Benefits Of Using Our BigQuery API

Data Integration

Powerful API with data normalization capabilities, data loaded will be provided in a consistent and immediately workable format. Access to granular data at any given moment, no coding necessary. Connect with previously soiled data streams and self-empower for deeper analysis.

Un-Rivaled Data Quality

Integrate and obtain quality data with ease and access to all the advanced features of BigQuery for enhanced operational performance. Handle data like never before; perfect results to meet all the business needs. Access features and data that is a class apart by in the industry.

Comprehensive Reports

Seamlessly operation by leveraging data, data ready to be explored, visualized and presented in easily digestible dashboards and reports. A single API for all your business data requirements, no need of multiple log-in for accessing quality data. Efficient and dynamic approach to reporting with more actionable insights for marketing and sales performance.

Multiple Streams

The BigQuery API by dJAX allows consumer to read disjoint sets of rows from a table using multiple streams within a session. This opens up options from distributed processing framework or from independent consumer threads within a single client.

Dynamic Sharding

Reduce tail latency by assigning data to streams dynamically. Remove the business need for complex load balancing with the API and if a stream inside a session didn’t receive a request to read the rows, there is no need for data to be assigned to the stream.

Column Projection

With the assistance of API offered by dJAX, at session creation, users can select an optional subset of columns to read. This allows efficient reads when tables contain many columns.

Filtering

BigQuery API allows options for users to provide simple filter predicates to enable filteration of data on the server side before transmission to a client. User interface with customized features for accessing quality data.

Snapshot Consistency

Storage sessions read based on a snapshot isolation model. All consumers read based on a specific point in time. The default snapshot time is based on the session creation time, but consumers may read data from an earlier snapshot.

Operational Value Of BigQuery API by dJAX

• Raw Data Querying: BigQuerry is a database hosted in the cloud. Access every options and integrate data sources with it through an efficient API. Raw data coming in through the API will be hit-level data. For simple marketing Google Analytics interface data is sufficient, the data obtained through GA is session based and is aggregated.
• Connect Data Sources: Data from other sources are only a glimpse into the data-driven industry and it is now much help while taking digital marketing, content, and usability decisions. With such a large amount of data, there’s always a question about where it should place. The API offered by dJAX makes it easy for you to integrate the data sources, thereby making it effective and efficient in handling data based operations.
• Data Into BigQuery: Using BigQuery API, access advanced options offered and it will be a single source for entire data. For example, imagine that you have a CRM. You can configure your website to pass in the Google Analytics client ID into your CRM when a customer record is created. This identifier is unique to every visitor on your website. Once the client ID is in your CRM, you can export your CRM data into BigQuery through the API.
• Connect BigQuery with your System: Exporting data from BigQuery is made simpler with the advanced options available in the API. Send data to from the database to any data warehouse that accepts CSV import with this API. For example, we might want to summarize web behaviour for each customer in a platform. We could easily obtain the original source/medium information from BigQuery and export it to the platform.
• Data Export for Visualization: At dJAX, we love that BigQuery API offered by us can integrate with many other data tools. These data form a virtuous cycle, which can help in better understanding of full customer journey. If the dots are connected, the value of all data is amplified. But perhaps the most virtuous cycle of all is the connection between Google Analytics, Google BigQuery and Google Data Studio. There is no better way to visualize analytical data.
• Combine Dimension: With BigQuery API from dJAX there are no limitations when it comes to dimensions. The GA model is structured so that session-based dimensions (like source/medium) don’t play well when combined with user-level or page-level dimensions and metrics. And there’s a limit to the number of dimensions we can see side-by-side: two dimensions is usually limit in the interface, five in custom reports, and the API allows for seven dimensions. With BigQuery, there are no such limitations.