OVERVIEW
Data is everywhere. With the spread of social media, the Internet of Things and digital business, data is dramatically increasing in volume, velocity and variety across business organizations.
This presents a great deal of opportunity. The more insight you have into business operations, client behavior and market trends, the better equipped you are to optimize all areas of your organization.
But that wealth of data also presents a wealth of challenges. With so much of it coming in, how do you organize it, analyze it, interpret it and turn it into actionable insights?
Collecting data is only the beginning. Data management, processing and analysis are complex tasks that require the right tools, resources and methodologies in order to turn your data into a truly valuable resource.
How should businesses approach this? Some opt for an in-house approach. But that is an expensive route that exposes the enterprise to several additional risks and cost.
Data Science as a Service (DSaaS)
A democratic approach to data
Effective business demands democratic analytics. Meaning, analytics must be accessible to all management levels. Access to real time information, analytic insights, metrics and actionable information should be accessible to the entire team.
Consider a top-down approach where a monthly or quarterly analysis report is prepared by a data scientist for C-level management who then disseminate the information to the rest of the organization. This approach puts limitations on the organization that hinder initiative and innovation.
A Data Science as a Service approach helps organizations to integrate data from multiple sources, democratizing access to data and its insights, empowering all levels to problem solve, innovate and identify opportunities.
Why not manage data analytics in-house?
To achieve the in depth and highly flexible level of data insight provided through data analytics requires significant investment. You would need everything from a qualified professional to the right infrastructure setup to a software license, and much more.
This makes in-house data management expensive and risky. On the other hand, contracting a Data Science as a Service (DSaaS) significantly reduces risk and complexity. It is easy to implement, delivers immediate results and has the flexibility to be used for multiple projects and initiatives.
Benefits of DSaaS
The ultimate objective is to help you reach your business goals by leveraging the wealth of data you already have. That data is filled with potential and opportunities that can be brought to light with the right tools. Through DSaaS, you and your organization will be empowered to learn from the past and present, make accurate predictions for the future and make highly informed business decisions.
Through DSaaS, you will be able to transform your data into information, and information into knowledge. Knowledge that helps business leaders answer their most challenging questions, such as:
- Which customers are most likely to churn in the coming months?
- Which products need to be restocked in each store and when?
- How many potential customers are likely to arrive at a hotel or restaurant without an existing reservation?
- What equipment may require maintenance before the service period?
- Which products have the highest cross-selling potential?
- What is the ideal holiday sale pricing on seasonal products?
- What are the optimal delivery routes to reduce delivery costs?
Meet the PROXIMITEAM Data Science Team
Our team is made up of highly qualified Data Architects, Data Scientists, Statisticians and Software Engineers with studies and certificates in Data Science, Statistics and Software Engineering among others.
Our team’s combined decades of experience in data management, predictive modelling and machine learning is dedicated to helping businesses and organizations make the most of the wealth of data at their fingertips.
Feel free to drop us a line if you want to learn more.
