Titel presentatie[Naam, organisatienaam]

Touring Day – SoftwareTour

Grace Accelerate GRC

The problem

Legacy Business Intelligence (BI) Platforms: The BI and analytics platform market is in the middle of an accelerated transformation from BI systems to platforms that also support analysis, prediction, forecasting and optimization.

Big Data Growth: The core problem is the emerging use of Big Data.

Data Integration: Big data and data integration are strongly connected.

No Time for Analysis: According to a recent TDWI study, over 60% of respondents say that they spend too much time on data collection, validation and reconciliation.

Excel Wars: Nearly 70% of financial departments do most of their work in Excel.

Radical new Architecture

GRACE uses a radical new architecture and

develops Data Mining software that combines artificial intelligence, machine learning, statistics and innovative database systems

is based on Data Science principles and highly advanced algorithms to extract knowledge and insights from data

enables the end user to create Analytics

Current Stage of Technology

GRACE has been under development for 3 years and

• 16 mining modules are developed

• 6 multinational corporations tested, evaluated and validated these modules

• GRACE provided analytical insights into Big Data in the following markets: Banking, Healthcare, High Tech, Consumer Intelligence, Government and Telecom

Key Novelty

GRACE technological innovation is disruptive in three distinctive ways:

• Self-learning data connections which avoids large investments in data analysis and maintenance

• Mining algorithms are incorporated into mining modules

• GRACE enables end-users to browse and discover company data

Performance Impact Dashboards

Added Value in High Tech Industry

Grace Systems proved added value on:

Engineering Maturity• GRACE is capable of applying real-time analyses of the engineering maturity aspects in Design-Build-

Operate-Maintain. We correlate failure, cause and effects over production lines, building blocks, maintenance engineers, design steps and time

Performance management on sensor data• Sensor data like maintenance and inspection evaluation of complex systems is often unstructured data

and not necessary coupled to design and production systems. GRACE is able to perform machine learning on unstructured data by using text mining e.g. electrics, gas and hydraulics

Predictive Maintenance and Reliability Engineering• In a cyclic analysis environment GRACE is able to contribute to the improvement of the reliability of

complex production systems by predictive outcome

Performance Benefit on Business

Grace Systems proved performance benefits especially on unstructured data:

Avoid Customization in ERP/BI and reduce costs by 75%:• High Tech industry companies do not have the ability to use standard ERP and BI systems for their uniquely

complex needs. Existing suppliers such as Siemens cannot deliver insight in risks from unstructured data streams. With GRACE it is possible to generate analytical insight on unstructured data without customization of default ERP/BI software which can be extremely costly and risky to implement

Reduce Analysis and Implementation time by 75%• Time is costly in industry processes because the TTM (Time To Market) dictates the timeline. High Tech

technology works with projects that are based on product designs and launches. GRACE is able to analyze data in real-time and so to provide relevant information to the different teams when needed. This dramatically reduces time in generating analytical insights

Award winning 2016

Achievements in the industry