How to become a data analytics consultant

If you’re thinking of becoming a data analytics consultant, you will need more than just the technical acumen you may have in data analysis, data science or data engineering. You may even be considering a career change from another data or statistically focused role. Your readiness and ability to step up to analytics consultant largely depends on your experience, and in working and communicating with other parts of the business. Working in cross-functional teams helps you learn the various skills of a consultant. In this post we cover the skills, understanding and experience you’ll need to be a successful analytics consultant.

Analytics consulting skills

Consulting skills are critical for understanding a company’ strategy and business objectives, communicating effectively, and delivering actionable recommendations. Below is a summary of consulting skills essential for this role:

• Problem Solving: Consultants are problem solvers at heart. Skilled at critical thinking, you dissect complex business issues, identify the root cause, and propose solutions based on data.
• Communication: Explaining complex data insights to non-technical stakeholders is a key part of the job. You must translate technical jargon into clear, concise, and actionable recommendations through data storytelling.
• Project Management: You will often handle multiple projects simultaneously, each with different timelines, objectives, and stakeholders. Effective project management is crucial to meet deadlines and deliver results.
• Stakeholder Management: you will need to be able to influence key stakeholders by clearly communicating the full value and ROI of your actionable data insights. You will manage relationships and regularly deliver clear and powerful presentations to an executive audience.
• Teamwork: Collaborating with a diverse team of professionals is a given in this role. It’s crucial to understand, respect, and leverage the strengths of each team member.
• Continuous Learning: As the field of data analytics evolves, so should you. Keep up with the latest tools, new technologies, and industry trends to maintain your competitive edge.

What background do I need to be a data analytics consultant?

Your background may come from within the technology or data and analytics ecosystem but not necessarily; you may have transitioned in from another field, such as science, maths, business or humanities. Most employers will value:

1. a degree and/or graduate qualification with training in a logical or scientific discipline of some sort. Statistical training is essential because it is the language of data.
2. relevant experience of 5-10 years, preferably across multiple industries.
3. familiarity with a range of relevant tools, software technologies and data architectures across the analytics ecosystem.
4. significant experience in business and analytics strategy. You need a good grasp of the ‘why and what’ when pitching a project.

Understanding the data analytics ecosystem

Effective data analytics consultants comprehend the complexity, growth and interconnectedness of the analytics ecosystem and are well versed in the processes used to generate insights from big data. Analytics ecosystems cover people, processes and technologies. If you’re ready to become a consultant, you will understand and have worked alongside people in the roles that contribute to the data analytics consulting practice:

• Data Engineers, Solution Architects & Data Operations Analysts: These are the people who design, build and maintain the data infrastructure and data services.
• Data Analysts: Analysts delve into the data, using statistical techniques to derive information and insights that can help support business decision-making.
• Data Scientists: These professionals use statistical knowledge combined with technical skills and AI techniques to identify patterns and trends. They also develop algorithms for predictive models. Data scientists use advanced analytics techniques.
• Business Analysts: They bridge the gap between data and business, translating data insights into actionable business strategies.
• Data Visualisation Experts: These experts turn complex data into clear, compelling visual representations, making insights easier to understand and act upon.
• Data Managers: Data managers and data stewards supervise an organisation’s data to ensure its accuracy, accessibility, and security. They oversee data collection strategies, maintain data quality and standards, and ensure compliance with relevant laws and regulations. They play a crucial role in implementing data governance principles.

Understanding each of these roles helps you to communicate effectively, appreciate their challenges, develop and foster a collaborative environment.

Experience with data analysis processes

The process of extracting information and insights from data sets is a repeatable and agile method among experienced analytics consultancies. An agile insights production process requires the analytics team follow steps such as these:

1. Work with the business interface to identify potential business use cases.
2. Then, an agile process is used to:
   1. Ingest data and explore it in an iterative discovery phase to identify and prioritise potential insights
   2. Validate insights by:
      • collaborating closely with business stakeholders
      • calculating ROI, deployment costs and business gains of actionable insights
      • preparing data visualisations and business proposals
3. Finally, validated insights are presented to business decision-makers and if approved they are deployed.

Analytics insights are produced with well- defined processes.

Knowledge of data and analytics solutions

Data analytics has a vast landscape of technologies and solutions available to do everything from building a data warehouse and big data platforms, to data management, data science and visualisation services. Analytics consultants are usually familiar with various technologies and architectures, such as:

• Snowflake: A scalable, cloud-native data warehousing solution with minimal management.
• DataBricks: A cloud platform streamlining big data processing and machine learning.
• Azure Analysis Services’ data modelling and interactive analysis capabilities.
• Power BI‘s comprehensive suite of business analytics and reporting tools.
• AWS Redshift‘s petabyte-scale data warehousing service.
• Tableau‘s interactive visualisation capabilities.
• Spark‘s versatile analytics engine.

Responsibilities of a data analytics consultant

The responsibilities of an analytics consultant may vary depending on the specific project, size of the company, analytics team, clients, and industry. For example, larger teams may have specialists for some of these tasks. Regardless, below is a list of common tasks that analytics consultants typically undertake or manage in their role:

1. Client Consultation: Engage with clients to understand their business objectives, issues, and data needs.
2. Project Scoping: Define the scope, objectives, and deliverables for analytics projects, ensuring alignment with customer requirements.
3. Data Gathering: Collect data from various sources, such as databases, APIs, or external datasets, and ensure its quality and relevance for analysis.
4. Data Cleansing and Preparation: Process, clean, and structure data to make it suitable for analysis, including handling missing values, inconsistencies, and inaccuracies.
5. Data Exploration and Analysis: Conduct exploratory data analysis to identify patterns, trends, and relationships in the data.
6. Data Visualisation: Create clear and compelling visualisations of data analysis results to help clients understand the insights and their implications.
7. Recommendation Development: Translate data insights into actionable recommendations to help clients make informed decisions, optimise processes, or achieve their goals.
8. Presentation and Reporting: Communicate project results, insights, and recommendations to clients and stakeholders in a clear, concise, and persuasive manner.
9. Project Management: Manage multiple projects simultaneously, ensuring they are completed on time, within scope, and meet customer expectations.
10. Team Collaboration: Work closely with business stakeholders, data analysts, data engineers, data scientists, and other team members to ensure smooth project execution and share knowledge.

A focus on the client

The best consultants will be totally focused on understanding the needs of the client and creating competitive advantage for them. They are aware of the pitfalls of too much focus on tools and methods. Successful analytics consulting services and projects enable the client to make better business decisions. Your expertise is brought in to help, so everything you do needs to build trust; their win is your win and customer satisfaction drives repeat business and referrals.

Industry experience

Data analytics consultants often have expertise in more than one industry. It means you can work for a broader range of clients and have knowledge of how things data can be done in other ways. Most exciting for your career prospects is that data analytics has broad applications across almost every industry. Below is a list of projects that demonstrate this diversity:

• Retail: Analysing customer behaviour data to enhance personalisation and improve customer retention.
• Healthcare: Predicting patient readmission rates based on historical data to improve patient care and reduce costs.
• Finance: Detecting fraudulent transactions by identifying anomalous patterns in transaction data.
• Manufacturing: Optimising supply chain efficiency using predictive analytics to anticipate demand and reduce waste.
• Transportation: Improving route efficiency by analysing and predicting traffic patterns.
• Marketing: Segmenting customers based on purchasing behaviour to target marketing campaigns more effectively.

These are just a few examples. The possibilities in analytics consulting are virtually limitless, making it an exciting, fulfilling, and impactful career choice. Remember, your journey into analytics consulting is a marathon, not a sprint. Stay curious, keep learning, and embrace the challenges – they are the stepping stones to your future success.