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Datamatics Data & Analytics Services help build intelligent solutions for data-driven businesses. Datamatics offers Data-to-Intelligence or Data Analytics solutions and services with the ‘Intelligence-First’ principle at the core to advocate true ‘Data Democracy’.
Datamatics Data and Analytics Services enable companies to work with high-volume multi-structured data including, structured, semi-structured, and unstructured by using Big Data and Analytics solutions.
Datamatics Data and Analytics Services enable businesses augment large, diverse data sets to discover patterns, correlate data-points, and uncover hidden insights. With the most prevalent use in consumer behavior analytics, predictive analytics, and AI/ML-enabled forensic data research, Datamatics enables businesses to scale to the next level.
Facilitate easy storage, linkage, traceability, and retrieval of data across the data lifecycle
Establish data governance model for storage, management, access, and analytics within a secure environment
Ensure cost-efficient data consumption along with high levels of data searchability and traceability
Generate real-time business insights by re-configuring Big Data sources and data storage
Institutionalize on-cloud or on-premise data models as required
Integrate Big Data platforms with data visualization tools
Engage next-generation visual analytics. Gain insights at the finger tips.
Use self-service analytics for 360-degree data analysis
Engage an intuitive and interactive data visualization platform
Use interoperable data visualization to create on-demand and customized dashboards
Gain competitive edge with data analytics across the descriptive, diagnostic, predictive, prescriptive spectrum
Perform faster data validations
Perform enhanced time series analysis
Perform deep analytics using complex, distributed architectures and advanced data modelling techniques
Big Data refers to extremely high volume datasets that require special storage platforms and processing tools. Given the extremely huge data size and data variations by the minute, Big Data can be analysed over a time series to discover trends as well as unearth patterns and associations.
Big Data Analytics is the use of specific advanced analytics techniques on big data or extremely high volume dataset to generate business insights. It starts with data collection through pre-defined templates and forms, followed by data curation, data processing, through data analysis. It allows to process structured, unstructured, and semi-structured data, join the dots to see the bigger picture, and to take data-driven, informed decisions.
Data Lakes are huge, centralized data reservoirs, which allow to store structured, unstructured, and semi-structured data at scale in As-Is format and from where different analytics programs, machine learning sequences, visualizations, and dashboards can be launched for better business decision making.
Big Data Analytics taps into huge data reservoirs to generate business insights. Visualization tools, such as TruBI, allow users to work with high data volumes and thousands of concurrent users to graphically represent data and bring out the underlying data story. The interactive visual elements allow users to understand the trends and patterns in the data and pinpoint the outliers.
Big Data and Big Data Analytics provide the vast datasets and analyses for TruAI, in specific, or AI / ML algorithms, in general, to learn from and generate sharper insights, which are not evident from slicing-dicing and analytics.
Big Data Analytics and AI/ML are symbiotic. AI/ML learns from Big Data and Big Data Analytics to get better at unsupervised learning and decision making. While Big Data Analytics leverages AI/ML to offer vivid analyses and better decision making power.
The combination of Big Data Analytics and AI/ML can be used holistically in all data-intensive sectors, such as Banking, Financial Services, and Insurance (BFSI), Healthcare, Communication, Media, and Entertainment (CME), Education Technology, Manufacturing & Supply Chain Management, Energy & Natural Resources, and Government & Public Sector Units.
Big Data Analytics Services over the Cloud offer the most benefits for data-intensive practices, such as Research & Analytics. It offers a scalable digital platform for parallel data processing, real-time analytics, stream data processing, context-sensitive analysis, inter-geography collaboration, and operational cost reduction.