As federal agencies pursue artificial intelligence (AI) at the enterprise-level, they must deal with greater volumes, velocity, and varieties of data. In response, the Accenture Insights Platform (AIP-IQ) for Government is adding big data processing platform Databricks to its powerful suite of data management tools to assist.
The pairing of AIP-IQ with Databricks capabilities helps federal agencies scale AI across critical mission areas. It allows data scientists to spend more time focusing on delivering insights and outcomes, instead of wrangling increasingly larger and complex data sets.
Ultimately, AIP-IQ with Databricks can help the federal government drive down development costs and risk while increasing value and agility.
What is AIP-IQ?
AIP-IQ is Accenture’s platform-based solution that enables federal agencies to rapidly create and update mission-specific analytics and AI solutions. These solutions can deliver significant impact at a lower total cost of ownership.
It is fully supported by Accenture Federal Services and enjoys FedRAMP authorization at the moderate level. For data scientists, AIP-IQ gives on-demand access to scalable clusters, enabling them to adjust memory and compute needs on the fly to address big data questions.
Leveraging its open architecture, AIP-IQ is incorporating Databricks in response to an expanding need for data ingestion and analysis across a range of federal use cases, including in fraud detection, healthcare analytics, life sciences, supply chain optimization, and open-source intelligence. These uses are shifting from siloed on-premise data management to more accessible infrastructures as the volume and variety of data grows.
At the same time, emerging data uses - including machine learning, computer vision, and other forms of AI – create demand for flexible and scalable approaches to compute and store. These demands require new models that reduce the effort needed to deliver processing and exploitation at scale.
Databricks can help agencies quickly scale their computing environment in response to these changes.
We saw the government’s need for scalable, flexible data processing during the COVID-19 crisis, as federal agencies shifted rapidly from management of text-based medical records to data-rich sources such as X-rays. That transition highlighted the need for more efficient, automated means of managing the data lifecycle.
Databricks and AIP-IQ Combine to Deliver Scale
The combination of AIP-IQ and Databricks vividly illustrates cloud’s power to perform data science and model deployment at scale, driving agility up and cost down.
Cloud offers the ready scalability government needs to adapt to fast-changing data usage scenarios. Agencies need to be able to address emerging data needs without having to reconfigure entire processes, and without requiring data scientists to become both cloud practitioners and Linux administrators.
By leveraging the data analytics power of the PySpark and Scala languages, Databricks helps analysts ingest, pre-process, and analyze data, as well as train new algorithms, all from within the same interactive notebook interface.
One key attribute here is repeatability. With Databricks and AIP-IQ, agencies can maximize the value of existing data processes, leveraging automation to readily fine-tune and redeploy as new data needs arise.
AIP-IQ with Databricks Boosts Data Capabilities with Lower Investment and Risk
AIP-IQ’s platform-as-a-service approach enables Accenture to rapidly and effectively incorporate new tools, wherever we see opportunities to enhance government’s use of data. Through the incorporation of Databricks, the platform is well-positioned to further drive such improvements by taking the complexity out of data transformation and by automating many labor-intensive tasks.
AIP-IQ is already utilized across the federal government as a comprehensive solution for AI, analytics, and data management, boosting the value of data to federal agencies. The addition of Databricks is a natural evolution towards managed services that provide federal agencies access to the tools they need, without increasing the burden of technical investment and risk.