Our Services
Seamless data solutions to gain vital insights. In today’s digital world, businesses must take advantage of big data sets and generate targeted, meaningful insights. Large sets are difficult to consolidate, standardize and manage, yet necessary for successfully generating critical intelligence about your business. Orion’s data scientists have developed user-friendly data science programs that your teams can integrate into their workflows.
Data Modernization
Modernization begins with business value. Create a value chain map that clearly identifies opportunities that result in outcomes that impact the top and bottom lines. What is the associated data that will help generate those outcomes. Prioritize the potential areas where data can elevate business processes, whether it’s increasing sales or reducing risk. On improving business processes and driving efficiencies, then creating a data lake should be at the top of your IT to-do list. If your focus is CX and you’re creating features and experiences associated with your product, the focus should be on cloud and scale.
Discover MoreData Accessibility
Modernizing data is essential for realizing the promise of AI. If historical data isn’t stored in an accessible way, AI and machine learning efforts are doomed to fail. Relevant questions include: How easy is it for data scientists to access all kinds of data that exists within the organization and How readily are they able to experiment and fail fast. Modernization begins with business value. Create a value chain map that clearly identifies opportunities that result in outcomes that impact the top and bottom lines.
Discover MoreFeatured Engineering
Data modernization requires a SWAT team—people with business expertise partnering with full-stack developers and others who understand the required sources of data. And given the multiplicity of devices, it’s vital to incorporate a design-thinking process to make data more accessible and meaningful. Using drone imagery, we provided advanced analytics (Artificial Intelligence and Machine Learning) to provision the tracing and prediction. To onduct environment monitoring and recording in an offline mode, which allowed them to traverse geographies.
Discover MoreData Ecosystem
A data ecosystem refers to a combination of enterprise infrastructure and applications that is utilized to aggregate and analyze information. It enables organizations to better understand their customers and craft superior marketing, pricing and operations strategies. A modern big data ecosystem, sometimes referred to as a “technology stack,” contains three fundamental elements: a responsive data architecture, delivery at scale and AI-driven intelligent data management. A cloud-first, AI-driven modern data ecosystem enables an organization to generate maximum business value from its unique data assets. Among the specific business benefits of data ecosystems
Discover MoreData Mining
Data mining is the process of examining large databases to determine patterns in data. This field is a combination of statistics, advanced analytics and artificial intelligence (AI). Data mining helps companies make informed decisions about future products or service offerings, and improve their business processes and customer engagement. While analytics is associated with generation and dissemination of insights and foresights at an industrialized scale, data mining for business analytics occurs in the innovation and experimentation stages, where data scientists and analysts find hidden patterns in data and test business hypotheses.
Discover MoreDeep Learning
Deep learning is a specialized form of machine learning that is powered by neural networking. It makes sense of unstructured data by extracting and classifying images or sounds to draw valuable business conclusions. Deep learning can be applied in areas such as facial recognition, speech recognition, translation, autonomous cars and social network filtering. Applying deep learning technology can reduce the amount of time it takes to analyze data and draw conclusions. It can also increase the quality and accuracy of those results. Deep learning technology algorithms are capable of learning without guidelines, eliminating the need for well-labeled data. Deep learning models can identify even very small product manufacturing defects that humans often miss.
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