10 Most Important Skills for BI Analysts

Who is a BI Analyst?

There are several tasks that outline who a BI analyst is.

The BI analyst collects the data, prepares and models it, stores it, analyzes it, and visualizes it.

Yes, it’s true that BI analysts do all that. But is it that distinctive? Many other data team members do most or all of these things. So, how is a BI analyst different?

Well, I already mentioned that, and you should always keep this in mind when thinking about BI analyst work and skills: turning data into information + strategic decisions.

How do they do that? By doing all the tasks I mentioned above. And how do they do them? By applying several main sets of skills.

Skills BI Analysts Need

Four main skill categories distinguish a real BI analyst from a would-be one.

1. Technical Skills

There are three main technical skills BI analysts need to possess.

BI Analyst Skill #1: Statistical Data Analysis and Interpretation

BI analysts use statistical analysis to interpret data trends. Interpreting data generally requires BI analysts to recognize patterns, anomalies, and correlations within it.

To do so, you need to be proficient in statistical analysis. In case somebody asks why, I can really only answer by asking: How do you imagine you can analyze data other than with statistical analysis? By crossing your fingers and wishing the data somehow analyzes itself? (Yes, I know those are actually two questions. One of them is reeking of sarcasm, which I apologize for.)

Let’s first have a look at the statistical concepts and then the tools you can leverage in practice.

Here is an overview of the statistical concepts you need to know as a BI analyst.

Statistical Data Analysis and Interpretation Skill Required for BI Analysts

Tools for Data Querying and Analysis

Knowing those statistical concepts is not enough; you also need to put them into practice using several common tools.

The three main tools BI analysts need to query and analyze data are SQL, Python, and R.

BI Analysts Requires Tools For Data Querying and Analysis

SQL: This programming language is a bread and butter for anyone wanting to query relational databases and extract data. BI analysts, of course, need to do that before they can start with data analysis. SQL can also be used in some statistical analysis, but not for such sophisticated calculations as Python and R can do.

Python: You can also query data with Python via its connectors – such as PyMySQL, MySQL Connector, psycopg2, and SQLAlchemy – for querying relational databases. However, its main strengths are data analysis, along with machine learning, and data visualization. Here are several Python libraries you’ll find useful for all these tasks:

1. Data manipulation & analysis

2. Machine learning

3. Data visualization

R: This programming language is designed for statistical analysis and visualization. No wonder those are its strengths. Here are several libraries that enhance R’s powers.

1. Data manipulation & analysis

2. Machine learning

3. Data visualization

BI Analyst Skill #2: Business Intelligence Tools

BI analysts need to be – no wonder! – comfortable with using BI tools.

BI tools help BI analysts with the following tasks:

Business Intelligence Skills required for BI Analysts

The main purpose of the BI tools is to visualize data and make dashboards so that non-technical users can more easily use and understand the data.

All the preceding tasks are basically subjugated to this one main task—data visualization. However, great visualizations are underpinned by thoroughly consolidated and aggregated data that’s been meticulously analyzed.

While visualizing such data might seem easy, it’s far from it. Choosing the right charts for particular data and knowing how to present your insights most efficiently is a skill in itself.

Some of the most commonly used BI tools you’re expected to know are:

BI Analyst Skill #3: Database Management

BI analysts need a solid knowledge of database structures, data warehousing concepts, and ETL (Extract, Transform, Load) processes. Why? You need to know how data is stored and managed and what data sources are there so you can query it and derive insights from it.

Database Structures and Management Systems

Knowing database structures involves understanding how the database and tables within it are structured. You need to know about columns and rows, primary and foreign keys, constraints, indexes, and database normalization. This is all to reduce data redundancy while improving its integrity and database performance.

Tools for Database Management

Tools that help you with that are Relational Database Management Systems (RDBMS) or, colloquially, just databases. Here are some of the more popular ones:

Data Warehousing Concepts and ETL Processes

For BI analysts, it’s important to know what data warehouses are and how they work. You should be familiar with the fundamental concepts, such as data marts, operational data stores, star, snowflake, and galaxy schema.

You should also know what OLAP stands for (Online Analytical Processing) and its operations, e.g., slicing, dicing, drilling down/up, and pivoting. This knowledge will be very useful in analyzing data in multiple dimensions.

Regarding the ETL processes, you’ll most commonly be involved in the T part of ETL – transformation. This stage involves cleaning data and transforming it so it’s ready for analysis. However, being familiar with the whole ETL process is helpful, as sometimes BI analysts will automate ETL processes and workflows so that data in the data warehouse is updated and maintained.

Tools for Data Warehousing and ETL

The tools BI analysts often need to be at least familiar with are:

2. Business Acumen

For businesses, having a great statistical analysis doesn’t mean anything on its own. They need actionable recommendations from BI analysts, and for them to provide them, BI analysts need to have strong business acumen.

This usually boils down to these two skills.

BI Analyst Skill #4: Industry Knowledge

When talking about industry knowledge, this usually relates to these three aspects.

I. Knowing the Industry Trends: First, BI analysts must understand the industry in which their company operates. They need to keep up with industry trends, which might include technological ones, changes in consumer behavior, regulatory changes, and so on.

II. Understanding Challenges: In every industry and a single business, challenges come from many directions. They can come from the competition, so BI analysts need to be aware of what the competitors are doing. The challenges can also come from, for instance, supply chain disruptions. Think of the problems the automotive industry faced after the COVID-19 pandemic, when there was a shortage of semiconductor chips due to increased demand. Or another example a shortage of qualified workforce. These are all aspects BI analysts must take into consideration when providing insights and recommendations.

III. KPIs: The Key Performance Indicators may vary from industry to industry. Knowing which KPIs to track to measure the company’s performance best also plays a role in giving sensible recommendations.

BI Analyst Skill #5: Strategic Thinking

The ability to think strategically has the same purpose as business acumen, only more within the company itself.

There are two most important aspects of strategic thinking that BI analysts need to show.

I. Aligning Data Insights With Business Strategy: There’s no point in giving recommendations to your management board only to realize your recommendations are going against the company’s strategy. So, as a BI analyst, you must be in the loop regarding the company’s strategic goals. From there, you can select the most relevant data for your data and provide deeper insights through your analysis. Finally, and most importantly, your recommended actionable strategies align with the company’s.

II. Case Studies: The case studies of strategic decision-making based on data analysis give you practical examples of implementing data models in actual business situations. From the case studies, you can learn from other businesses’ success and failure stories. That way, you can tweak and refine your own strategy.

3. Soft Skills

The soft skills complement the BI analyst’s technical skills and business acumen.

These are the three most important soft skills.

BI Analyst Skill #6: Communication

We already brushed this subject when we talked about data visualization, which is one way BI analysts communicate with various stakeholders. However, it doesn’t end there. BI analysts also need to write reports and participate in meetings. In both cases, they must translate their insights into understandable language and express themselves clearly.

When you look at it, BI analysts need to be vital in communicating in three forms: visual, written, and spoken.

BI Analyst Skill #7: Problem-Solving

In the broadest sense, solving problems is all BI analysts do; analyzing and visualizing data are means to that goal. As a BI analyst, you need to think analytically (as expected from the job with the word ‘analyst’ in its name!) so you can break down problems into logical segments. You need to identify the problems clearly and, from there, use data in a way that will result in robust and practical solutions to the business problems.

BI Analyst Skill #8: Collaboration

BI analysts often work on projects that involve cross-functional teams. This could include fellow data team members as well as people from other departments, such as marketing, financial analysis, sales, and even management. Different backgrounds require a BI analyst to be adaptable to different communication styles, perspectives, and personalities. That way, you can achieve cross-functional integration and coordinate with the stakeholders to finish the project on time and within budget and specifications.

Of course, it helps if you can build good working relationships and people actually don’t think you’re impossible to work with.

Continuous Learning and Adaptation

This is less of a skill and more of a general approach BI analysts should have towards their jobs and skills. It’s a cliché, I know, but BI analysis really is a quickly-paced field. It possibly applies to most other jobs.

Regarding the BI analysis, continuous learning and adaptation mean these two things.

Continuous Learning and Adaptation Skills for BI Analysts

BI Analyst Skill #9: Staying Current With Technologies

BI analysis as a field is driven by technology. It’s developing quicker than ever, so today’s state-of-the-art tools in BI analysis can quickly become insufficient, even obsolete, in a couple of years. As a BI analyst, you need to keep up with technological developments and learn BI tools and programming languages, which we have already mentioned.

In doing so, try also not to jump from one all-rage tool to another. The balance between knowing the tools that are the industry standard and being familiar with the latest developments is important.

One important aspect of that is keeping up with AI and machine learning. They are here to stay, so ignoring them would be foolish. This technology is already used in automated data analysis and predictive analysis, which helps improve decision-making and efficiency.

How do you keep up with technology? By taking courses, attending seminars and conferences, getting certifications, and even attending university for a degree.

Another way is to be immersed in the community by reading relevant articles and publications, participating in professional forums, and following industry leaders on social media.

BI Analyst Skill #10: Flexibility in Adapting to New Business Needs

BI analysis is not the only thing changing; businesses are, too. These changes also impact how BI analysts approach their jobs.

Business objectives evolve constantly for various reasons: change of business direction, change of management board, change of owners, or any given reason. BI analysts have to adapt to these changes and part with the yes-but-we’ve-always-done-it-this-way mindset.

In practice, this means BI analysts must always be ready to customize their analyses and reports.

Their business acumen will also help them anticipate future trends and business needs. This will make their analyses more likely to stand the test of time by making them easily adaptable to changes in future requirements.

Conclusion

These ten skills are necessary for anyone aspiring to be a (good!) BI analyst. As you saw, it requires a good mix of technical skills, business acumen, and soft skills. On top of that comes the mindset that drives you to learn continuously and adapt to changes in the business world.

We at StrataScratch can help you build your technical skills and business acumen. Actually, you can do it yourself; we only provide coding and non-coding interview questions. As you practice, don’t forget to use our blog, as it’s a valuable resource for explaining many technical concepts BI analysts need to know.