As a trusted partner we offer a wide variety of services ranging from architecture design to data science best practices. With Tan-sol you can out source all or parts of your data function.
Data Engineering
Data engineering as all about Building Data pipelines and automation and ensuring improved data quality, security, data processing, and delivering data to your organization in a meaningful format.
Business units typically find that they lack sufficient data to support their assumptions and data driven decisions. This is usually due to soiled data, non-frequent data or a lack of support from IT functions to deliver the data they require.
Without having the sufficient data at their disposal, a backlog and lack of innovation is created. We have 15 years combined experience in delivering data solutions fit for purpose, from production environments to analytical purposes.
We do this by developing our solutions on leading cloud providers, integrating with existing systems, file pickups, database migrations, API integrations or other on premise systems. Our solutions typically take the form of a csv, bespoke, scalable solution that runs in either real time or batch frequencies.
Further alerting can also be configured to ensure a problem is identified and rectified early on. This ensures data is always available in a high quality state in order to empower data driven decisions by end users.
Data Migration
Solution overview The Tan-Sol Data Migration Readiness Assessment service is designed to help organizations complete data migration projects on time and within budget.
With the Tan-Sol IT expertise Services, this service provides insight into the requirements and data migration challenges, prepares organizations for the transition, and identifies appropriate actions using best practices and technologies.
Key features and benefits of Data Migration
Insight into existing environment:
The service provides organizations with key knowledge about their current storage and SAN configuration, helping them understand the potential challenges of a data migration project. The insight allows organizations to better prepare and plan for the migration process.
Transformation and Transition:
The service helps organizations understand the possibilities for transforming and transitioning their legacy storage environment. The process builds confidence in the migration process and helps ensure that the organization is well-prepared for the transition.
Best practices-based Data Migration:
The service works with organizations to identify the appropriate actions needed to complete successful data migration, leveraging Tan-sol tools, methodology, and technologies based on best practices while facilitating an efficient and effective migration.
Effective architecture/methodology:
The service helps define a more effective architecture and methodology for the data migration project that aligns with the organization's essential business needs. This helps ensure the migration is optimized for performance and meets the organization's requirements.
Data Visualization
In the Era of " Big Data" kicks into high gear, visualisation is an increasingly key tool to make sense of the trillions of rows of data generated every day. Data visualisation helps to tell stories by curating data into a form that is easier to understand, highlighting the trends and outliers. A good visualisation tells a story, removing the noise from data and highlighting the useful information.
However, it's not simply as easy as just dressing up a graph to make it look better or slapping on the "info" part of an infographic. Effective data visualisation is a delicate balancing act between form and function. The plainest graph could be too boring to catch any notice or it could make a powerful point; the most stunning visualisation could utterly fail at conveying the right message or it could speak volumes. The data and the visuals need to work together, and there's an art to combining great analysis with great storytelling.
AI & ML (Artificial Intelligence and Machine Learning)
ML and AI is a Voyage
We specialize in ensuring your machine learning project sees the light of day in a production environment.
Use cases stretch far and wide, young and old such as credit risk scores to chatbots. Our customers typically engage with us from a project inception phase until a project monitoring phase to ensure project success. Machine learning projects can seem daunting to organizations new to this field, we work with our clients to ensure as much transparency and assistance in order to empower them for best in class results.
We develop bespoke solutions and tailor them according to the specific use case, this means that we develop transparent models if applicable or highly complex models for maximum accuracy. We typically deliver these models in API form either in real time or batch response times.
We have a combined experience of 16 years in the area of machine learning and data engineering, ranging from use cases in the finance sector, e-commerce, insurance, IOT, retail and travel. Due to the complexity of machine learning solutions, when needed, we tailor the end product in a way to deliver and allow for configuration by extracting the complexities away from the end user.
Enhance your business with AI & Machine learning
Machine Learning can be complex but in fact machine learning is very demanding in regards to data quality and size. We have a pragmatic approach to ML and would not advice our clients to go this route unless we certain you are ready.
We have deployed with several projects in Machine Learning and predictive analytics. Below you can see some of the business problems we have experience with
Customer Lifetime Value (CLV)customer lifetime
Developed a model used to determine a long-term value for each customer.
Applications Personalized Marketing and Customer Retention
Prediction of car theft
Developed a predictable model using telematics data to predict whether a vehicle has been stolen or not.Used in the centre to prioritize contact and work
Churn predictions
Developed a model to predict whether a customer will terminate his contract with a company in the near future Used to focus efforts on retaining customers at risk to end the relationship
Customer segmentation
Analyzed customer and transaction data to create customer segments to identify additional sales and cross sales opportunities, as well as understand different customer segments.
Financial forecast
Developed an economic forecasting system, used for budgets, enabling input from sales managers and senior executives along with external factors. Further included forecast models on outstanding balance, opening volume and sales as well as outstanding debt.
Strategies Data Cleaning Prediction
Model Developed a predictable model to predict the right brand and model and use output as input for reporting dashboards across the enterprise, as the source data contained too many errors to effectively report on.
Scorecards for bad debt
Developed a predictable model to provide an estimate of the probability of recovering 80% of
a consumer & outstanding debt.
Bad Debt Pricing Model Developed a predictable model to provide an estimated value of a
bad debt for debt collection companies or companies to bid for a reasonable selling price of
their bad debt
Location and route algorithm
Developed a custom algorithm using telematics data and predicting a vehicle's home and
workplaces.
Used to determine how far vehicles drive from origin to points of interest, cost reduction and
risk
Cloud Migration
We has brought various companies from no data competencies to databases and dashboards in the cloud, providing the opportunity to take advantage of Machine Learning to improve the business.
We Typically Work with the major cloud providers such as
Azure
AWS
GCP
