The transformative potential of artificial intelligence (AI) for businesses depends on access to high-quality data. As organizations strive to harness AI's transformative power, understanding and executing effective data preparation protocols is paramount. The ability to access and fully use corporate data set is a critical determinant of a company's success in harnessing AI.
How easily can you get your data?
Many organizations prepare data for AI using manual processes such as coding. Those further along the modernization path use
ETL or
ELT solutions. Precog, an AI-powered data replication (
ELT) platform, has fully automated the
ETL/ELT process. This involves a few key steps:
- Establishing a connection to an API through specific web requests
- Handling authentication
- Handling pagination
- Interpreting the API’s response to extract and normalize the data (this normalization transforms complex data schemas into a structured SQL format suitable for loading into data warehouses, facilitating BI and ML applications).
- Loading the data into a data warehouse or database.
Precog automates these steps, drastically reducing the time and errors associated with manual coding and significantly enhancing the efficiency of data integration tasks.
Data connectors: all or nothing
Through its platform, Precog offers a suite of connectors encompassing the entire SAP ecosystem and leverages AI and machine learning to streamline the creation of
data connectors for every SaaS API. As the only mainstream
ELT vendor to fully leverage AI, Precog delivers powerful no-code integrations that require no custom code or ongoing maintenance. It also features native integrations with
SAP Datasphere and
SAP Analytics Cloud and supports popular data destinations such as
Snowflake,
Google BigQuery,
Redshift,
Kafka,
Microsoft SQL Server and
Postgres.
Fully automated replication
Precog’s data integration platform empowers businesses to easily connect, transform, and analyze data from
SaaS API sources, delivering valuable insights for smarter decision-making. The platform enables fully automated connectors for APIs, accessing all endpoints and datasets, extracting data, and using machine learning to normalize it—automatically identifying primary keys. The platform also supports incremental data loading, allowing users to set refresh schedules according to their needs. The result is a robust, automated data pipeline that efficiently transfers data into any
data warehouse or
database, seamlessly managing custom fields, data types, and type adaptations.
Conclusion
The journey to AI transformation is complex, yet with the right tools, it becomes manageable and attainable. Precog’s
ELT solution equips businesses with the essential infrastructure to harness the power of their corporate data assets, enabling the delivery of robust AI-based solutions. By embracing Precog, companies can transform their data into actionable insights, driving growth and success in the AI era.