Globalization of supply chains has led to growing legal, safety, security and product take back concerns. Through supply chain analytics, we are able to give you an in-depth view of each link in the supply chain to help your organization create a strategic plan to increase efficiency and maintain a competitive advantage. Innovations in analytics allow companies to collect and analyze information throughout the global supply chain in near real-time to identify and take advantage of opportunities to increase efficiency, responsiveness and resilience, while decreasing shipping delays, inconsistencies with suppliers and other inefficiencies. Through supply chain analytics, we help clients:
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We assist our clients in identifying the business metrics they need to order to achieve a singular view of the customer experience with Cattain-IT you can Cattain real-time insights and actionable metrics.
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Companies that invest in marketing analytics as a “discipline” can measure, manage and analyze performance to maximize marketing effectiveness and optimize return on investment (ROI). At DataFactZ, we bring more than a decade of business analytics experience and a marketing analytics team headed by Ph.D.s who can build and optimize state-of-the-art simulation models. Our strengths in statistics and mathematics, simulation, modeling and optimization provide the most effective analytical foundation to address complex business and strategy issues. As our approach to advanced analytics is interdisciplinary, we can draw from other areas in customer analytics in order to complement marketing analytics, such as customer life value, customer retention, or upsell and cross sell. The strategies mentioned above provide only a basic foundation that should be complemented by several other areas in advanced analytics, in order to establish a successful marketing analytics strategy, such as:
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Risk intelligence (RQ) uses forward-looking risk concepts and tools to make better decisions, alleviate threats, capitalize on opportunities and create lasting value for companies. Organizations with high risk intelligence tend to make more informed business and security decisions than those with low RQ. We are at the forefront of helping organizations use advanced analytics for risk management. Organizations want to harness data that is locked in silos and a variety of external sources. We build advanced analytics systems to give organizations clearer visibility into the challenges associated with managing many types of risk in key areas such as operations, regulatory compliance, supply chain, financial services, e-commerce and credit.
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Social media continues to evolve as a powerful networking platform, generating massive volumes of data and tremendous opportunities for organizations to take their CRM capabilities to a new level. But organizations are struggling to effectively tap into these platforms to gain a better understanding of their markets, customers, and competition. Capturing consumer data from social media platforms empowers organizations to understand attitudes, opinions, and trends, and manage their online reputations. At Cattain IT Labs, we help organizations build social media analytics strategies that go beyond traditional monitoring methods. Our solutions use advanced machine learning and natural language processing (NLP) techniques to offer customized solutions for various business initiatives.
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Designing a scalable real-time analytics model is a step-by-step process involving multiple tools and technologies. There is no single tool that provides a complete solution. One approach to solution development is Lambda architecture. This approach takes advantage of both batch and stream-processing architecture to provide a balance among latency, throughput and fault-tolerance. It uses batch processing to provide comprehensive and accurate analytics on entire data, while simultaneously using real-time stream processing to provide incremental analytics on the continually arriving data. The two analytics results are then merged to generate a comprehensive overview of insights. Lambda architecture describes a system consisting of three layers: Batch layer – for batch processing of all data Speed layer – for real-time processing of streaming data Serving layer – for responding to queries The below diagram illustrates an example of designing a scalable real-time analytics architecture.
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