Dive Into the New Age of Accelerated Analytics
Data Analytics and Data Science can be put to a wide range of uses limited only by the imagination of the business people and technologists so it can sometimes be difficult to visualise just what data science can do and how it can benefit each organisation.
Exactly the same machine learning algorithm can do things as diverse as detect the difference between mines and rocks in a minefield, predict whether two people could be compatible partners or detect whether a wine is red or white without ever seeing the wine or the label.
In fact the challenge can be working out where the potential and possibility overlaps with each organisation, hence The Knowledge Ladder have summarised below just a few examples of where data science has been used to deliver tangible improvements to business outcomes.
High End Data Visualisation Dashboards
The Knowledge Ladder worked with DN Group to compress and pivot millions or rows of source data from their Virtual Learning Environment and then link it to their student records system.
This has provided an unparalleled insight into how the VLE is used by courses, areas, students and teachers, has identified areas of best practice to promote and areas that need additional support to achieve consistently outstanding outcomes and has delivered recognised business benefit.
Membership Segmentation
This project involved working with the Chamber of Commerce to maximise their subscription memberships.
Data describing existing member location and industry sector was overlaid and matched to market data to identify sectors, locations and other factors with high growth potential leading to significantly improved volumes of subscriptions and memberships.
Customer Retention
An innovative machine learning algorithm was developed that sifts through customer data examining a wide rang of factors that predict whether customers are likely to churn (i.e. leave) or stay.
Customers predicted to churn are then given intervention and support to reduce the churn rate and this work is projected to deliver a £200k per year return-on-investment and to benefit the local economy by £477k per year.
The video clip below provides an overview of some of the approaches and principles involved ...
Sentiment Analysis
An organisation with 750+ employees approached The Knowledge Ladder to help them to analyse qualitative feedback from the free text comments questions of staff surveys. The text was analysed using advanced technology including the IBM Watson AI engine to produce details of how the respondents were feeling when they wrote the responses. This was then linked to word clouds and the question responses to provide instant, online, interactive analysis.
The result was the conversion of unstructured textual feedback into meaningful analysis leading to the implementation of changes that improved staff health and wellbeing.
Strategic Planning
In this project Lincoln College had access to economic data about employer job adverts and to academic data about the types and levels of qualification delivered but there was no way to link and compare the two.
The Knowledge Ladder carried out an advanced analysis to enable the comparison of supply and demand which was then fed into the strategic planning process.
The result was improved outcomes for employers and students enabling the college to deliver on its mission to be "Employer-led; producing a highly skilled and productive local workforce".
Realise the potential of data analytics and data science to solve your business issues and improve outcomes.
These are just a few of the successful projects The Knowledge Ladder has helped customers with representing some of the potential areas where data analytics and data science can solve problems and add value for organisations.
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The opportunities are endless and there are almost certainly affordable, accessible and agile data science projects that The Knowledge Ladder can help deliver to solve problems and improve outcomes in your organisation.
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Get in touch today to start your data science journey ...