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Optimize Processes and Enable Data-Driven Decisions

Big Data Analytics can turn your streaming operational data and historical data archives into a competitive advantage. No matter the volume, growth rate, diversity or complexity of your data, we can help your organization leverage the right tools to process this data at the edge, in-stream, or in central databases transforming it into self-service data visualizations for users across your organization. A well-designed Big Data strategy will improve your time to action, improve system reliability, optimize the customer experience, and eliminate costly manual activities through AI and machine learning processes.

In this rapidly evolving field, we will guide you in applying the following technologies to improve your business:

AI-Augmented Capture


AI-Augmented Capture is a data analytics solution that takes content capture to the next level. Leveraging artificial intelligence (AI), it improves business processes by augmenting capture with institutional knowledge derived through machine learning to automate classification, entity extraction and routing at scale. Information is captured from content in documents and routed to the appropriate workflow, based on context and priority, from the moment it enters the enterprise.

Robotic Process Automation (RPA)


RPA allows companies to emulate and automate the actions of humans to execute business processes. By using Alitek’s Robotic Process Model, our customers deploy “bots” to assist with the capture of high-volume incoming communications while interacting with AI processing tools to streamline processes. RPA robots utilize the user interface to capture data and manipulate applications just like humans do. They interpret, trigger responses and communicate with other systems in order to perform on a vast variety of repetitive tasks. Only substantially better: an RPA software robot never sleeps and makes zero mistakes.

Text Mining for Sentiment Analysis with OpenText Magellan


Hearing the voice of your customer is a challenge in the information rich environment.  OpenText™ Magellan™ is a flexible artificial intelligence data analytics platform that uses Natural Language Processing and unstructured data analytics, such as text based data mining, to easily include unstructured data and facilitate advanced analytics solutions, such as sentiment and emotion analysis tools.

Big Data Analytics with OpenText Magellan


OpenText™ Magellan™ is a flexible artificial intelligence data analytics platform that combines open source machine learning with predictive analytics and self-service analytics to analyze big content made up of structured and unstructured data stored in enterprise data management platforms and external sources. Magellan leverages artificial intelligence to offer additional specific solutions focused on improved decision making, automation, and business optimization.

In-Stream Analytics at the Edge with Kx


Kx is the leading IoT and streaming analytics platform in the world and with its ultra-small platform (800 KB), the Kx’s kdp+ can operate at the edge of your network and within the streaming environment to provide real-time analytics, data aggregation, and sub-second decisioning. Kx enables your systems to stream sensor data at high frequencies and volumes directly into a kdb+ time-series database. This allows for efficient data usage enabling an immediate response to equipment and sensor conditions.

Featured Article:

In Stream Analytics are Optimizing Power Grid Operations

by Mike Brookover

In Memory Computing for Analytics with Kx


Processing the vast amounts of data in an analytics platform is a challenge for the traditional computing platforms.  The Kx in memory computing (IMC) capabilities enables organizations to reduce processing time for Big Data analytics by orders of magnitude leading to a direct improvement in your organization’s time to action.  Kx’s IMC enables high-speed analytics that traditional databases cannot match and provides the scalability to process the vast quantities of data needed for historical analytics, simulations, and training of machine learning algorithms.

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