Attova and Real Status Ltd. will show how a 3D realtime modelling software like Hyperglance can form part of a visualisation reference architecture in Financial markets for competitive advantage.
Within financial markets, business, trading and operations expect immediate access and transparency to information that can be explored, manipulated and acted upon.
Whether applied to collaboration, analytics or modelling real- time data and infrastructure, leading companies who harness visualisation will be in a position to profit from getting it right. A rapidly growing discipline, visualisation enables financial services organisations to communicate more effectively , improve speed of analysis of real time or historical data and better understand the impact of IT infrastructure to their business.
Filip Greenwich, Director, will highlight a framework and reference architecture in financial markets where visualisation supports key CIO objectives including disseminating knowledge to users, employee productivity and effectiveness and business process improvement.
This will be followed by a Hyperglance demo by Stace Hipperson, CTO, to support this reference architecture at the operational layer.
Hyperglance from Real Status uses 3D visualisation and navigation technology to create a real-time model of a mid-size or larger enterprise's IT estate, whilst overlaying performance and financial metrics. This enables IT management decisions based on business impact rather than technical whim.
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3. The greatest value of a picture is when it forces us
to notice what we never expected to see.
—John W. Tukey. Exploratory Data Analysis. 1977.
4. Background
• Unstructured and structured data volumes
continue to grow exponentially, giving rise to a
new type of ‘knowledge infrastructure’
• Regulatory changes dramatically affecting data
requirements
• A new era of big data is also emerging
• Its application will be a key way for leading
companies to outperform their competitors
• Technology Advancement
5. Background
• Increasing the use of Information/Analytics,
business process improvement and reducing
enterprise costs will continue to remain top
business priorities for CIO’s
( Gartner annual CIO Survey- A Time Of Great IT Transition)
6. Business Challenges
• Business: lack of visibility to all data
• Trading: Analyse and correlate complex data in real-time to
maintain competitive advantage
• For Managers: reducing costs, improving efficiencies and improving
productivity
• For IT – understanding the impact to technology in changing
business decisions
7. Business Challenges
How can financial institutions make sense
and profit from the huge amounts of data
across their business layers?
8. Visualisation
Visualisation refers to the innovative use of images and
interactive technology to see , explore and share large
quantities of information in new and meaningful ways
9. Visualisation
• Data visualisation is in the middle of a remarkable
growth phase.
• Proven to contribute impressively to improvements
in business user insight, productivity and adoption of
‘dashboarding’ ( preferred medium for visualisation)
(TDWI Best Practices Report 2011)
10. Visualisation
• Two main categories of data visualisation
– Visual reporting ( defined by metrics and time series
information)
– Visual analysis ( explore data to discover new insights)
– ( filter, compare and correlate at the speed of thought)
– (statistical, forecasting, what – if and predictive analytics)
• Also focus on
– Visual modelling
– Visual collaboration
11. Visualisation- Infrastructure
Modelling
• Automatically builds 3D Maps showing the
relationships between application and
infrastructure
• Aggregates and visualises existing
performance data on the model in real time
• Decisions and priorities are based on
business impact
12. Mass Market
• Wall Street Journal offers free service with
Interactive Graphics
Source: www.online.wsj.com
13. Mass Market
• NY Times offers readers
Visualisation Lab
• Amateur investors have at
their disposal a rich array of
interactive charts to analyse
both individual stock
performance and market
trends
• Visualisation is helping to
influence stock purchases
by ‘main street’ investors.
Source: www.nytimes.com
14. Visualisation in Financial Markets
• Differentiate and distinguish from the quality of their service, their
understanding of their customers or speed at which they can win ( Insight,
know-how and know-when)
• What if-analysis to help clients understand the effects of changes in
investment decisions
• Monitor and manage risk across geographies
• Dynamic report generation
• Find market trends first
• Audit order execution, market spreads, costs and trading behaviour
• Build guided analysis flows for portfolio management
• Build customer portals for investment performance
15. Visualisation in Financial Markets
• Trade data analysis ( spot anomalies for compliance)
• Monitor market, credit & counterparty, liquidity , fund risk management
• Latency Monitoring
• CEP monitoring
(Source: linedata/lab49)
16. Visualisation Benefits
• Make faster, more accurate and informed decisions
• Efficient – Correlation of large data sets at the speed of
sight
• Meaningful-data in context rather than tables or lists
• Make sense of unstructured data and feed it into
decision making and process improvement activities
• Making strategy real – Overcoming information
barriers and decision control
17. Visualisation Challenges
• Never a plug and play solution
• One size does not fit all
• Vary by
– Type of user
– Purpose ( strategic, tactical, operational, cultural)
Customisation, collaboration and iteration are
required for organisations to operate interactive
visualisation solutions that deliver maximum
benefits
18. Visualisation Challenges
• Visualisation requires Foundational EIM and
Information Automation disciplines
– Master Data Management
– Data Quality
– Integration
– In-memory, distributed and cloud-based
infrastructure
– Visualisation rendering and interaction tools
19. Approach
• What does the business need?
• Who Are We Addressing?
• What is the information management mandate?
– Master data management & data quality
• Technology Choices?
– Build v Buy?
– Top Down v Bottom Up v Middle Out?
20. Approach
Viewing visualisation as the new decision support lifecycle
• Seven Stages of visualising data
• acquire, parse, filter, mine, represent, refine and interact.
• Very important that each visualisation best suits what you
want to convey about your data set
21. Recommendations
• Focus on requirements first
• Deliver High Quality Data
• Intuitive Interface that supports an infinite class of
visualisations
• Prototype/Proof Of Concept
• Know Your Users
• Iterate
• Apply visualisation best practices
• Less Is More
• Zero To Three
22. Attova’s services
Mission is to drive visualisation the front line of most customers
businesses
Maturity Assessment Model-
Data, Enterprise, Leadership, Technology, Analysis
- Visualisation Novice
- Localised visualisation
- Visualisation adoption
- Visual Organisation
- Visual competitor
23. About Attova
• Partnership with Real-Status in financial markets to enable customers to
make rapid infrastructure decisions based on business impact- define,
design and deliver a real-time infrastructure visualisation solution
• Launched in 2011
• Offers high performance business consulting & technology services into
financial markets
• Knowledge Network- a powerhouse of efficient, experienced and expert
level independent consultants and performance technologists
• Compelling operating model
– Multiple solution options for client- flexibility and choice
– Ability to precisely align the resource & technology to the solution
– Define, Design, Deliver- single port of call
A graphic display can only develop the sort of forceful personality Tukey suggested when it is prepared carefully. As we shall see, when the combination of interesting data and clever display are properly aligned, remarkable outcomes can result.
An enterprise knowledge infrastructure is a comprehensive ICT platform for collaboration, knowledge sharing and learning with knowledge services built on top that are contextualized, integrated on the basis of a shared ontology and personalized for participants networked in communities that fosters the implementation of KM instruments in support of knowledge processes targeted at increasing productivity of knowledge work.Regulation- Market in Financial Instruments Directive ( Pre/Post Trade Transparency or Best Execution)European Market Infrastructure Regulation ( stability within OTC derivatives markets) ( central counterparty clearance and reporting to trade repositories)Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.Big data refers to large data sets that become difficult to work with through traditional database management tools and raise challenges around capture, storage, search , sharing, analytics and visualisation. The benefits of business working with large data sets includes being able to spot business trends,
while organisations are making headway on enterprise information management and broad analytics solutions,much potential insight is buried within static reports that are accessible only by a small fraction of the organizationBusiness: lack of visibility to all data coupled with limited options for manipulating and exploring masses of data affecting their business and innovationTrading: Now expect to analyse and correlate increasingly complex data and monitor trade performance across multiple asset classes and liquidity venues in real-time to maintain competitive advantageFor Managers: reducing costs, improving efficiencies and helping employees making well-informed decisions thus improving productivity For IT – understanding the impact to technology in changing business decisionsWe are highlighting business challenges right across the enterprise
Well, visualisation is a discipline and a solution that can help businesses with those challenges and at multiple layers within the business
A recent report carried out by the TDWI where the majority of the respondents were in financial services illustrated that data visualisation significantly improves business insights and user productivity ( which includes accelerated time to insight) and increases user adoption of BI tools.74% of respondents rated the influence of data visualisations on business insights to be very high or high and 67% felt that data visualisation had a very high/high influence on productivity
Whilst most efforts are currently focused around visualisation for reporting an analytics there is also a growing demand for visual modelling and collaboration solutions
Visualisation is very pervasive . As illustrated here, the wall street journal and NY times are offering visualisation solutions to their subscribers…
To give them the ability to analyse a number of different scenarios from market trends to individual performanceBy giving these individuals more insight, visualisation is helping to influence stock purchases by ‘main street’ investors.
Whats the purpose of visualisation in financial markets?There are many different applications at many different layersIt can provide multiple levels of insight and understand throughing visualising multiple different scenarios internally across the business layers or externally to improve client relationships
Market Liquidity analysisCab provide a rich framework to gain insight and market dynamicsConsolidate trade reports, quotes and order books in real-time, creating a single virtual order book that represents the liquidity of the entire visible marketYou can visualise best execution across multiple exchangesYou can visualise real time fixed income portfolio pricing You can visualise grid computations based on grid/cpu/disk io through to back testing workloads and mortage pricing workloads
Break down information barriers- bring in multiple data sources and use visualisation to put analytics. Modelling , collaboration and reporting into the hands of the people making the decisions
Insight from visualisation solutions will only be as good as the underlying data.Entity level relationships need to be understood at the structural level in order to achieve correlations and associations at the business level.The worst case scenario is for analysis to yield wrong conclusions based on faulty dataSource data cannot be inconsistent or dirtyOrganisations are adopting tiers of trust zones for data and acknowledging lack of control over external and unstructured data is acceptable as part of the analysis as long as stake holders are aware.You also need the ability to link multiple data sources into the dashboard of information to be visualised, If a cloud solution is seen as a potential source, then an external integration as a service platform could form part of the technology landscape ( Boomi, Pervasive)Infrastructure is required to support large volumes of data- this can be achieved using column based compression optimisation , map reduce or elastic scale of operating environment. Allow high performance computing characteristics at low cost.
Whilst visualisaton can yield tremendous benefits to an organisation, important to realise value of a strategy in managing decision support Understand the business purpose ( then know which techniques are applicable)Understand the audience ( understand the intended usage- to guid scope and design)Understand the information management mandate ( master data management and data quality are crucial parts of the visualisation story). You can address information management through a maturity assessment model, rather than through a series of redundant or divergent effortsExplore: Tool decisions based on existing technology footprints and expected use casesWerehighlihting simply one of these today and will continue to highlight a number of technologies over a series of events.
Acquire-Obtain the data whether from a file on disk or a source over the network ( structure data on the server to facilitate retrieval of common subsets)Parse- Provide some structure for the data’s meaning and order it into categories(string/float/character/Integer/Index)Filter- Remove all but the data of interestMine- Apply methods from statistics or data mining as a way to discern patterns or place the data into mathematical contextRepresent- Choose a basic visual model – bar graph, tree, heat mapRefine- Improve the basic representation to make it clearer and more visually engagingInteract- Add methods for manipulating the data or what features are visibleThis should be enabled via existing vendors and solutions or designed
Attova’svisualisation services helps organisations see and understand their data for competitive advantageThrough our consulting services and partner alliance we allow organisations to add meaning & content to their data by creating dynamic displays that connect directly to various data sources.Visualisation to action- push out to the front lines of the business. Putting the data at their fingertipsData/Technology Describe Your organisations dataHow does your companies data compare to that of the competitionEnterpriseHow would you describe the enterprise focus of your visualisation and analytics efforts?How extensively are your visualisation capabilities embedded into your tech and business decsion making processes?LeadershipHow active is leadership in supporting visualisation efforts?How well does a leadership model the behaviour of visual/analytic oriented cultureTechnologyAnalysis How would you describe the visualisation /analytic talent strategy in your organisationHow do you support the recruitment, development and retention of visualisation/analytical talent?