Avoid data swamp
New technologies have reduced the cost of storing massive volumes of data. While many organisations have embraced the ‘data lake’ concept, the reasons for storing massive volumes of data are often unjustified and seldom clear.
All too often, the data stored is unfit for purpose, lacking standardisation or duplicated. Sound familiar?
A data lake can easily turn into a data swamp that has significant overheads but serves little purpose.
Get your data fit
Imagine a platform that offers a practical way to stream, analyse and archive data to bring order to chaos. In an ideal world, your organisation would ingest data, analyse it in real-time, and store only what it needs to support the business.
With cloud and artificial intelligence, this is now possible. Data can be ‘strip-mined’ to determine which data sets are of intrinsic importance and need to be stored. It’s likely that you need only a fraction of the data you currently store.
New mindset and methods
Adopting this innovative approach may require new technology. But it also requires a new, confident mindset and methods that may be at odds with current thinking. GFT can help you with both.
We have unique practical experience of delivering smart data management solutions that straddle big data and traditional enterprise data. Our approach is groundbreaking and based on our own technology and methods.
We can help you develop a strategic approach to data that will deliver a quantifiable and sustainable improvement to your business. Our aim is to deliver tools and methods that will enable you to become self-sufficient in future.
Applicable wherever you want, wherever you need
Identification of patterns across transactions and recommendation of relevant products
Video intelligence surveillance, machine learning, (home) automation, robotics, and space exploration (MARS)
Ingest normalised real-time data and deliver measures of predictions from ML algorithms
Streamlining of business processes
Image recognition for mortgages and insurance
Email categorisation, entity recognition, sentiment analysis and routing
Analyse and assess data trends for selecting explanatory variables
Natural language processing (NLP) for document classification and entity extraction
Based on historic data, identify unusual movements
Analysis of behavioural models and dynamic customer segmentation to identifying core behaviours and patterns
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Streaming ingest and intelligent store
Unleash the full potential of your data by leveraging GFT’s streaming ingest and intelligent store
Data science accelerators
The GFT data practice helps meet the many challenges of a data science project on a daily basis.