The Aunsight Platform

Aunsight is a data analytics software platform. Data analytics is driving innovation in business, but it isn't easy. Aunsight provides both an infrastructure and a suite of tools to design, deploy, and operate data analytics projects. Built on top of industry standards like Hadoop, Spark, Apache Drill, and GraphQL, Aunsight delivers scalable compute and storage resources for getting big data projects done from start to finish using integrated tools that make developing these projects easy.

Why Use Aunsight?

Because everything is designed from the ground up to work together, Aunsight provides a seamless end-to-end solution for data analytics. Once data enters the Aunsight platform, everything is within reach and ready to go. From data import and ETL transformations to machine learning and data solution delivery, everything happens in Aunsight, minimizing costly IT roadblocks as data moves from one platform to another in the cloud. Because of this integrated approach, Aunsight offers an attractive alternative to the complexity and high cost of implementing a self-service big-data program using commodity-grade data services platforms. And because Aunsight's data center is System and Organization Controls (SOC) compliant, you can rest assured that your organization's sensitive data will be safeguarded according to one of the highest standards in the industry.

How it Works

The Aunsight platform offers a variety of tools that put the power of data analytics within reach of your team. Rather than relying on experts for everything, Aunsight provides a self-service platform with tools that enable your own team to manage as much of the process as you want. And of course, for everything else, Aunalytics is always able to provide support and consulting to help you achieve your goals with in-house data science and engineering experts.


Aunsight provides a flexible and adaptable data lake that accommodates data with varying degrees of structure to ease the data ingestion process. From highly-structured SQL databases to unstructured document stores to audio and visual media, Aunsight imports data into a private, hosted data lake using a flexible schema system that allows data of all sorts to reside in and be used by Aunsight's tools. Aunsight's dataset schemas help these tools understand and work with data in the stages that follow.


Aunsight automates the process of cleaning and preparing data with dataflows, a tool that automates the operations to be performed on datasets. As in most data analytics, Aunalytics relies on industry standard systems like Hadoop to manage the storage and compute resources for these transformations. However, rather than developing dataflows tied to a single technology, Aunsight dataflows are an abstract description of the data-cleaning process which is dynamically translated into the platform-specific query language used by the storage and compute resources. This layer of abstraction helps make dataflow creation simple and keeps analysts and data scientists focused on what they do best---working with data!---while Aunsight manages the infrastructure.


Just as dataflows automate the process of cleaning and transforming data, workflows automate and orchestrate the entire analytics pipeline. Aunsight workflows allow users to design a "flow" of components that define the different steps needed to transform data into insights. From automating data ingestion schedules to running ETL, applying machine learning models, and automating the delivery of insights, workflows manage it all from start to finish.

Workflows also provide a way to integrate custom user-written processes running in the Aunalytics platform compute infrastructure. User processes allow Aunsight to deliver almost limitless flexibility in tailoring what a workflow can do to specific client needs, no matter how complex. If Aunsight doesn't already do it, it probably can.

Machine Learning

Aunsight offers a robust platform for artificial intelligence and machine learning. Aunsight's Data Labs offers data a workspace for developing machine learning solutions in a user-friendly Jupyter notebook environment. These models can be trained and ultimately deployed as machine learning models as processes running on a compute cluster. And because models integrate easily into Aunsight workflows, users can automate the training, scoring, and pruning of model versions to obtain optimal results as new data enters the platform.

User Management and Security

Because data analysis requires exposing large amounts of a company's data to a data analytics team, data analytics projects need to ensure proper governance about access to data. For this reason, Aunsight provides powerful user management tools to keep data secure while allowing access to those who need it. Through its team and project management tools, Aunsight administrators can segregate data into separate contexts where project managers can manage access according to rules defined for those teams. In addition Aunsight's Secret Service makes it easy to grant team members permission to use secret data like API tokens, passwords, and encryption keys without actually revealing those secrets to members or in software code. Together, these tools keep data secure while making it easy to grant or revoke access to those who need it most.

Getting Started

Are you interested in getting started with Aunsight? Meet the tools:

The Web App

The Aunsight Web interface is the preferred method of interacting with projects and data for most users. The web interface provides a convenient, graphical interface to almost all the functionality of the Aunsight platform products. It also offers additional graphical features not available through other tools. Building dataflows and workflows, for example, can be done visually using drag-and-drop canvas editing tools. Rather than wrestling with the underlying text-based object ontology, users can create flows by adding and removing components through menus and immediately see the results graphically displayed. The web interface also offers a convenient way to search and browse through datasets in a way that cannot be performed by other tools.


For those who need to leverage the power of Aunsight from the command line or in shell scripts, Aunsight provides Toolbelt, a command line interface to the Aunsight platform. Toolbelt can perform all the functions of the web interface, but can be integrated into scripts in order to automate repetitive tasks and provide access to Aunsight in different environments

Aunsight SDKs

For developers and data scientists, Aunsight offers two software development kits (SDKs) for interacting with Aunsight using the Python or Javascript languages. One common use case for these SDKs is the development of machine learning models in Python-based Jupyter notebooks. The SDKs allow data to be fetched into notebooks where machine learning APIs like Keras or Tensorflow can be used to develop models. Another use case is to develop processes that extend what Aunsight workflows can do by developing custom processes. The SDKs can also be used to develop other data-rich apps that interact with the Aunsight platform from different contexts whether in Aunsight or from the Cloud.

Custom Tools (The Aunsight API)

In addition to the three standard tools for managing Aunsight, clients with specific software requirements may wish to craft custom tools that interact with Aunsight's RESTful API. Custom services can extend the Aunsight platform in a number of ways, giving almost limitless flexibility to what the platform can be tailored to do.


At the end of the analytics process, data consumers can view reports specially made for the Sightglass data delivery application. Business analysts can develop custom solutions that push data output to specified mobile users or groups, who then have access to data reporting and insights pushed to the client mobile app for iOS, Android, and the web.