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5 Skills Every Data Quality and Business Analyst in Financial Services Needs

Reading time: 6 min   |  By Sonia Chopra   |  Published in Articles,

A business is constantly growing and improving as customers, data, technological advances, and employees change. As a result, firms must learn how to successfully analyze and optimize their processes and data, improving both efficiency and quality. This is where both a business analyst and data quality analyst come in. While working towards similar overarching goals, there are specific skills each of them need.

In smaller companies, the business and data analyst roles are often combined or used interchangeably. For larger organizations, especially financial institutions, firms employ both (and multiple) to perform unique tasks and handle specific duties.

Before we dive into the particular skills that business and data quality analysts need, let’s define their responsibilities.

A business analyst monitors the organization’s needs, policies, processes, and operations for achieving business goals and increasing operational efficiency. They drive and provide actionable insights, analyses, and recommendations to the executives and stakeholders. They are also responsible for designing and building dashboards, visualizing data, and reporting insights for driving business growth and decision-making.

Data quality analysts examine and analyze complex data sets, communicating actionable insights and predictive trends to help businesses make informed decisions. They are responsible for ensuring end-to-end data quality across the landscape, which is key for managing risk and regulatory compliance.

5 Ways a Business Analyst Can Improve Their Performance

Business analysts have a wide variety of responsibilities surrounding both data and processes. If there are inefficiencies or errors, they must often make changes within the firm’s actual infrastructure and workflows. This is not an easy task, especially within complex business landscapes. Business analysts need the following skills to be successful.

Deep Technological Knowledge
Having extensive IT experience and knowledge is key for this role. Business analysts should stay up to date on industry and technological advances, because they work with specialized tools such as Business Process Management (BPM), Application Performance Management (APM), rules engines, etc.

Research, Research, Research
Research is essential for any business analyst. It is the first step when solving a problem, testing theories, and implementing a solution. Individuals must gather and analyze information daily. For specific projects, they must put together complete and thoroughly backed research to help others understand the problem, processes, and solution.

Data Analysis
Just gathering data isn’t enough for this role. Business analysts must be prepared to deep dive into complex data and processes, understanding gap analysis, financial planning, risk assessment, and statistical analysis. Additionally, they should be able to help organizations with their competitive advantage by properly interpreting and translating data into better operational and business strategies.

Organization and Documentation
Analysts must go beyond simply collecting and regurgitating information to other team members or stakeholders. Individuals must concisely organize and document every detail to seamlessly collaborate and explain projects, expectations, and limitations.

Problem-Solving, Solution Implementation
One of the most important skills to have as a business analyst is problem-solving. The role depends on developing solutions (often quickly) that solve critical business and operational problems. Being flexible, agile, and adaptable is vital.

5 Ways a Data Quality Analyst Can Improve Their Performance

Data quality analysts are more focused on the actual data within an organization. While a data quality analyst should have all the skills of a basic data analyst, there are a few specialized skills as well.

Technical Expertise
The data quality industry is constantly transforming and innovating. However, there are some technical components of the role, such as understanding data profiling, data discovery, information chain analysis, root cause analysis, exception management, cost-benefit analysis, ROI discovery, etc. The analysts should also be experts in data management, data governance, and of course, data quality. Additionally, they should be well versed in programming languages, data reporting tools, and statistical packages, in order to analyze data and communicate findings to stakeholders.

Industry Knowledge
There are so many data quality tools on the market. Therefore, it becomes vital that the analyst understands the competitive landscape and where their specific solution fits.

Problem-Solving and Critical Thinking
Data quality analysts must identify issues and implement solutions to improve their data’s correctness, completeness, consistency, and timeliness. They should be able to use their critical thinking skills to troubleshoot and resolve issues within their data, data sets, and workflows on a large scale.

Analytical Expertise
This role must work with large and complex data sets, applications, workflows, and systems. Therefore, strong analytical skills are needed to evaluate and interpret trends and insights.

Data quality analysts must be able to successfully communicate their findings to executives and stakeholders.

The PeerNova Cuneiform Platform

PeerNova’s Cuneiform Platform provides business and data quality analysts with the confidence they need in order to make better, informed decisions, while improving their overall operational efficiency and reducing risk. The solution measures data quality metrics and quickly prioritizes and resolves data quality exceptions. For more information, request a demo today!

By Sonia Chopra

Sonia Chopra is PeerNova's Product Marketing Manager for the Valuation Risk product line. She has nearly a decade of marketing experience and has been with PeerNova for eight years. She specializes in crafting content and campaigns that address the complexities of product and valuation control, such as market volatility, asset pricing discrepancies, and regulatory compliance issues. Her ability to articulate the intricacies of these challenges, enables her to develop highly effective product marketing strategies that meet the evolving needs of the industry.

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