Findings underscore differing perceptions of the efficacy of data architectures, data management, and even the data itself, for fuelling confident decision-making.
By Gary Allemann, MD of Master Data Management
A new report, The Future of Data Architecture Study, reveals major discrepancies in how data management and architectures are viewed across organisations. In general, while central analytics teams are satisfied with the future viability of their architectures, business users are unconvinced that existing architectures are able to meet constantly evolving business needs.
The report summarises the findings of a world-wide survey conducted in March and April 2022 by BARC (Business Application Research Centre), one of Europe’s leading analyst firms for business software. In collaboration with Precisely, the global leader in data integrity, the report focuses on the areas of data that targeted data and analytics leaders and C-level roles across several industries.
Business stakeholders do not trust data and analytics results
The report found a clear disconnect between Data and Analytics (D&A) teams and their key business stakeholders – with business users showing a lack of trust in the data and insights presented.
* 70% of business leaders do not believe that currently implemented data and analytics applications meet their needs.
* By contrast, only 32% of central D&A teams expressed concerns over their architectures.
* 52% of business stakeholders agree that existing data is not suitable for analysis, compared to only 36% of central D&A teams.
Key questions asked included:
* Are classic data architecture concepts such as the data warehouse, data lake, or data lake house viable for the future?
* What will work for today’s needs? What will we need in the future?
* What broader data architecture concepts are being pursued for the future, and what benefits are expected?
* What is new about data fabric compared to existing concepts, architectural approaches and technologies? Does data fabric play a role in future planning?
* Can a data fabric be successful without a data mesh?
Report reveals key data challenges
The research revealed key challenges highlighted by business managers, including extensibility of real or near-time requirements (41%), comprehensibility of the data landscape or architecture as a whole (39%), and flexibility of extended data requirements (32%).
The main drivers for modernisation are the optimisation of existing data models and processes, migration to cloud platforms, and efforts to improve the quality of source data or data interfaces.
Data-driven business leaders are increasingly focused on developing a robust data integrity strategy that will enable them to break down data silos, improve data quality and provide transparency. Ultimately, business agility is a key goal, along with improved decision-making, risk management, and compliance.
The report emphasises that, while centralised design paradigms, such as the data warehouse, remain the core of many architectures, further data siloes are sure to emerge due to the sheer volume of disparate data sources in play. Businesses must accept and manage this complexity and improve their source data, to streamline data pipelines and build a basis for data virtualisation.
Technology is not enough
Furthermore, the report agrees that technology alone is not enough. Companies must invest in understanding and maturing their data culture by bringing different stakeholders together to enable the exchange of perspectives and ideas.