scalability and consistency accross the organisation

Data is now recognised as one of the most important assets of any financial services organisation. A defined data strategy is accepted as critical for the long term success of an organisation. Once implemented, a data strategy will improve efficiency, help to manage operating costs, support global growth, enable rigorous risk management and enable reporting to clients and regulators.

Data strategy is central to investment management and can either be a powerful enabler for business operations or, if done badly, a significant barrier to growth. A successful data strategy will provide the vision and roadmap to advance the data operation from current state to a target structure, including implementation of a strategic data architecture, data operating model and data governance.

data strategy

Squalio data architects will help your organisation to develop data strategy that aligns with
and supports the business and IT strategies.



This phase includes identifying business objectives and needs, enlisting  stakeholders, defining scope and schedule, and discovering technology and data assets that have a role in the data strategy.



In this phase, focus primarily on current business processes, data sources, data assets, technology assets, capabilities, and policies. The purpose of this exercise is to help with gap analysis of existing state and the desired future state.


sTEP 3

This phase without a doubt will account for majority of the time in formulating data strategy. Analysis is focused on identifying gaps in data architecture, technology and tools, processes and of course people – their skills, training etc.


step 4

This phase includes the development of roadmap and strategy for change – dta governance, organizational and culture change, incentives etc.

Benefits of data strategy aligned to the business and IT strategy

  • Ensure the scalability required by the organisation.
  • Create consistency across the business for its data with coherent definitions, accuracy and timeliness to meet the business needs, including the demands of new instruments/products from a trading, operations and risk and compliance perspective.
  • Establish a fit for purpose platform for delivering data to business applications.
  • Remove duplication and inefficiencies in data management processes, thus creating a cost-effective data operation.
  • Provide data for client and regulatory reporting that the business can rely upon to be current and correct.
  • Minimise the data collection costs and the fees paid to market data vendors.

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