Combine data from structured and unstructured databases for data driven insights.
Empower users to collaborate and analyse data in different ways.
Collect and store data to leverage 70% savings on storage cost for data in data lakes. (aws.amazon.com)
AWS Data & Analytics Competency Partner
As an AWS Competency Partner in data and analytics, we showcase our ability to deliver scalable and efficient solutions for data-driven decision-making and business intelligence.
Harness more data, from more sources, in less time
Empower users to collaborate and analyse data in different ways to lead to better, faster decision making. With data lakes, you can store your data as-is, without having to first structure the data, and run different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning to guide better decisions.
As your business grows, data lakes have the scale, agility, and flexibility required to combine different data approaches needed within for a modern data strategy.
Data movement
Import any amount of data that can come in real-time and in its original format to be able to scale to data of any size, whilst saving time by avoiding data structures, schema, and transformations.
Securely store, and catalog data
Secure and store relational and non-relational data from business applications to IoT devices and social media. Identify and understand data by cataloging, crawling and indexing data.
Analytics
Run analytics without the need to move your data to a separate analytics system and allow various teams in your organisation like data scientists, data developers, and business analysts to access data with their choice of analytic tools and frameworks.
Machine Learning
Generate different types of insights including reporting on historical data, and doing machine learning where models are built to forecast likely outcomes, and suggest a range of prescribed actions to achieve the optimal result.
Modern Data Strategy
Building a data strategy is essential for organisations to stay relevant, competitive, and innovative amidst constant change. Because data is vast, dynamic and comes in many different formats, extracting value can be challenging and to harness data’s full potential requires an end to end modern strategy.
Data Maturity Assessment
The Data Maturity Assessment (DMA) is a 5 point assessment of specific areas contributing to a data strategy to highlight your current state, score your data maturity and highlight a clear roadmap for improvement.
