Are your data technology investments still leaving insights buried in reports?
Data has the potential to reveal game-changing insights, but those insights are only leveraged through definitive action. DataFactZ designs solutions that take your data insights out of the fog and into impactful decisions. With successful executions across various domains including financial services, retail and health care, our associates know how to surface your most important data in the most efficient way.
A holistic view of what data-driven decisions mean for your organization, encompassing the entire data lifecycle from discovery to operationalization.
The current landscape of Business Operations is rapidly evolving, making traditional BI implementations a thing of the past.
Businesses need a powerful and rapid delivery of analytics, right at their fingertips. With 17+ years of industry experience and a vast pool of talented resources, DataFactZ can guide your team to build a robust, resilient, and easily scalable BI system that enables self-sufficiency and accessibility for its users.
While Business Intelligence can obtain information from the past, Machine Learning and AI can predict the future. Machine Learning Algorithms train systems to identify patterns and anomalies, predict trends, and identify new opportunities. We can help to implement Machine Learning into new and existing projects.
Out-innovate your competition with a well-planned AI implementation.
Organizations are digging much deeper for answers and an efficient way of doing so, meaning the best time to invest in AI technologies is now.
Conversational analytics, machine learning, and predictive analysis have all narrowed the gap between businesses and data-driven decisions. With DataFactZ’s expertise across various analytics tools and cutting-edge strategies for implementation, our customers’ answers are never too far out of reach.
Various operational factors such as technological challenges, security, governance, compliance and success criteria make it difficult for organizations to deploy and maintain ML models at scale.
DataFactZ’s MLOps practice provides the following capabilities to your organization [while being cloud agnostic], ensuring reliable and efficient deployment and operationalization of ML models:
- Deploy ML projects from anywhere.
- Monitor ML applications for operational and ML-related issues.
- Capture the data required for establishing an end-to-end audit trail of the ML lifecycle.
- Automate the end-to-end ML lifecycle with Cloud provider-specific ML and DevOps services.
ML on Cloud
DataFactZ is a proud partner with all major cloud providers. Our certified team of data scientists and engineers can help you build, train, and deploy ML models quickly and at scale, or use preexisting models quickly and efficiently.
For teams without data science practitioners, DataFactZ’s Data Engineers can help your team create and execute models using standard SQL with the aid of tools like BigQuery ML.
Data science is a discipline that analyzes data from multiple sources to create meaningful insights. It is multidisciplinary including data mining, statistics, artificial intelligence, predictive analysis and more.
Data Science allows companies to utilize data collected to make business decisions, understand customer data to refine products or services.
Data Science can address many challenges in different service sectors, universally it can detect fraud, analyze customers, detect expired or malfunctioning products, forecast trends, and ensure compliance with regulations.
Having a data science platform makes it easier to dissect and utilize large datasets, eliminate bias through trusted analytics that can be audited or recreated, and deliver models faster with more accuracy.
Business intelligence (BI) refers to software that help companies collect, view, and analyze business data to complete tasks like decision making, and improving business processes.
Business intelligence utilizes either raw data or data warehouses that centralizes data from multiple sources, and implements BI software to develop reports, charts and maps as a way of visualizing and analyzing data.
There are many benefits of Business Intelligence technology including improved data accuracy, increased productivity, eliminating inefficient data, enhancing transparency, improved business operations and better customer insights.
Machine learning is using mathematics and data to help a computer learn the way a human would, without specific instruction. It is a division of artificial intelligence.
Machine learning has many benefits including, user experience to understand the customers preferences and optimize it, the ability to monitor for fraud, enhanced automation to lower costs, pattern identification that can help uncover insights.
Finance sectors use machine learning for fraud prevention, retail utilizes the ability to analyze buying patterns, healthcare uses it for diagnostics, patient monitoring, and outbreak prediction are some examples.
The potential of machine learning is to create meaningful business data and insights from the data they have. IT can centralize data science into a cooperative platform and simplify operations.