Data Management
Daskin Data Science and Analytics Australia can assist in the design, implementation and management of database systems. Database design and data models are important, as good database design supports ease of maintenance and quality of data, therefore quality of the results and analysis.
For Daskin Data Science and Analytics, data management is the process of collecting, storing and using data securely and effectively. The objective of data management procedures is to provide evidenced based decision making options to create value for customers and the organisation. A data management strategy addresses the activity of users and administrators, the capabilities of data management platforms and technologies , adhering to the regulatory requirements, and the needs of the organisation to generate value from its data. Customer data privacy and security and data policies are more important now than ever before in customer engagement and relationships.
Advanced Analytics
In addition to the traditional business intelligence (BI) techniques, Daskin Data Science and Analytics can apply more technical methods and tools to develop deeper insights from your data to support analysis and recommendations. If you are having difficulty in extracting and analyzing the information you need, advanced data analysis techniques can contribute to data-driven actions, such as:
Improved decision-making
More effective marketing
Better customer service
More efficient operations
For Daskin Data Science and Analytics, data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data and big data in various forms, either structured or unstructured. Data Science is a field that encompasses anything related to data cleansing, preparation, modeling and analysis. Data Science is an umbrella term for techniques used when trying to extract insights and information from data.
Daskin Data Science and Analytics has experience in advanced analytic techniques which include but not limited to data/text mining, machine learning, pattern matching, forecasting, visualization, semantic analysis, sentiment analysis, network and cluster analysis, regression analysis, multivariate statistics, graph analysis, simulation, complex event processing and neural networks in any analytics platform of choice.
Analytics as a service
Analytics as a service (AaaS) is the provision of analytics software and operations through web-delivered technologies. Daskin Data Science and Analytics can offer businesses an alternative to developing infrastructure just to perform business analytics. AaaS uses data mining, predictive analytics and AI to effectively reveal trends and insights from existing data sets.
Are you challenged by the constraints of your current resources to generate the insights you seek from your data? Then Analytics as a Service is an effective end to end solution. Analytics as a Service can accelerate the implementation and adoption of BI / Data Analytics into your organisation.