AI Business Analyst: Top 5 Tools To Master In 2024

AI is everywhere now and changing how businesses make decisions. It is even making business processes faster and more efficient, whether it’s predicting customer trends or automating repetitive tasks.

According to McKinsey Global Institute, businesses that use AI to analyze data see a 50-60% improvement in key business metrics.

But to really take advantage of this AI revolution, you need the right tools. And if you want to be an AI business analyst, you need to know which tools to use and how to use them.

Getting started usually looks too big of a task to do, but it doesn’t have to be. If you’re serious about being an AI business analyst, I recommend that you should check out this guide.

It has everything you need to get started and make the right decisions from the beginning.

Okay, let’s get into the top 5 tools every AI Business Analyst needs to know in 2024. But let’s first see why an AI business analyst needs the right tools.

Why AI Business Analysts Need the Right Tools

As an AI business analyst, your job is to help businesses make decisions that are data-driven. But with all the large amount of data out there, manually doing that is impossible.

That’s why the discussion of AI tools is important. They help you gather, analyze, and make sense of massive amounts of data.

Trust me, when you have the right tools in your hands, everything becomes easier. As reported by Gartner, companies leveraging AI for data analysis are able to make faster and more accurate decisions, enhancing their overall competitiveness.

Let’s break down why tools are so important for AI Business Analysts:

• Speed up data analysis: You’ll be working with huge data sets. Manually crunching those numbers takes forever. AI tools help you analyze data quickly so you can focus on providing insights.
• Automation: Imagine doing the same task over and over again. With AI tools, you can automate those tasks and have more time to work on bigger projects.
• Make better decisions: AI tools not only help you analyze data but also predict trends and suggest decisions based on that data. These tools are your secret weapon for making better business decisions.

Without the right tools, you’ll fall behind. But when you know them, you can give businesses the data-driven advice they need to succeed.

Top 5 Tools for AI Business Analysts in 2024

Now let’s get to the major focus of this article: the top 5 tools every AI Business Analyst needs to know.

Tool 1: Microsoft Power BI

Power BI from Microsoft is a business intelligence tool that lets you create interactive reports and dashboards. You don’t have to be a tech expert to use it, which makes it perfect for beginners.

With Power BI, you can:

• Visualize your data: Turn numbers into charts and graphs.
• Share with your team: You can create reports that your colleagues can interact with even if they don’t have Power BI.
• Analyse data from multiple sources: You can bring in data from Excel, databases, and other platforms into one place.

Why you need it: Businesses run on data and they need to see that data in a way that makes sense. Power BI helps you do that without the complexity.

Tool 2: Python

Python is one of the most in-demand programming languages. It’s widely used in the AI and data analytics world because it’s easy to learn but incredibly powerful.

As an AI Business Analyst, Python will be one of your favorite tools. It helps you with:

• Data analysis: Python can help you clean, organize, and analyze huge data sets with just a few lines of code.
• Machine learning: If you want to build models that predict business trends, Python is your sure tool.
• Automation: You can automate repetitive tasks like data entry or report generation with Python.

Why you need it: Python is essential for anyone who wants to do serious data work. And the best part? There are tons of free resources online to help you learn.

Tool 3: Tableau

Tableau is a data visualization tool that’s a bit more advanced than Power BI. It’s great for bigger data sets and more complex reports.

With Tableau, you can:

• Create interactive dashboards: Just like Power BI, you can turn raw data into interactive reports that anyone can use.
• Analyse data from different angles: Tableau’s visualizations are highly customizable, so you can find insights that might not be obvious at first glance.

Why you need it: If you’re working with big data, Tableau is one of the best tools to make sense of it all.

Also, many large companies already use Tableau, so knowing it will help your job prospects.

Tool 4: Apache Hadoop

Apache Hadoop is the tool you need for big data. Businesses are collecting more data than ever and that data needs to be processed, stored, and analyzed.

Hadoop is built for that. With Hadoop, you can:

• Process big data sets: Traditional systems can’t handle the amount of data many businesses are generating today. Hadoop lets you store and process that big data.
• Work across multiple machines: Hadoop spreads the workload across multiple machines so even if you’re working with a lot of data, it’s fast and efficient.

Why you need it: Big data isn’t going away. If you want to work with large companies that rely on data to make decisions, Hadoop is a must-learn tool.

Tool 5: SAS (Statistical Analysis System)

SAS is a tool for statistical analysis and business intelligence. It’s widely used in industries like healthcare, finance, and government, where companies need to make data-driven decisions as fast as possible.

With SAS, you can:

• Perform advanced statistical analysis: You can use SAS to run analytics on your data to uncover hidden trends.
• Build predictive models: SAS is great for forecasting future trends based on historical data.

Why you need it: SAS is used by some of the biggest companies in the world. If you want to be an AI business analyst, learning SAS is a good way to do it.

How to Get Started

Ready to get started with these tools? You can read more about it here.

Here’s a recommendation:

1. Microsoft Power BI: Microsoft has free tutorials on their website. You can also find YouTube videos that walk you through creating your first dashboard.
2. Python: There are tons of free resources online. Websites like Codecademy and Coursera have Python courses that are easy to follow, even if you’re a beginner.
3. Tableau: Tableau’s website has a “Tableau Public” section where you can practice building dashboards for free. They also offer certification programs if you want to prove your skills.
4. Apache Hadoop: Udemy and Coursera have beginner courses in Hadoop. Practice by working with big data sets to understand how Hadoop handles big data.
5. SAS: SAS has free resources and certification courses on their website. Start with the basics and work your way up to more complex analytics.

The key is to practice. Don’t just read about them—get practical experience by working with real data.

Challenges of being an AI Business Analyst

Like any career path, being an AI Business Analyst comes with its challenges. Here are some of the most common:

• Learning curve: Some tools like Python and Hadoop can take time to learn, especially if you’re new to programming or data analysis.
• Keeping up with new technology: AI is a rapidly changing field. New tools and updates are coming out all the time, so you need to stay up to date.
• Working with dirty data: In the real world, data isn’t always clean and easy to work with. Learning to clean and organize dirty data can be a challenge, but it’s a necessary skill for any AI Business Analyst.

To overcome these challenges, here are a few tips:

• Set aside dedicated learning time: Consistency is key. Even 30 minutes a day adds up over time.
• Join a community: Online forums, Reddit groups, or even LinkedIn groups can be great places to ask questions and get support.
• Stay curious: Technology changes fast and the best way to keep up is to stay curious and never stop learning.

The future of AI Business Analysts and tools

The role of an AI business analyst will continue to advance. As companies collect more data and AI technology advances, new tools will emerge and the demand for AI business analysts will only grow.

According to a report by PwC, AI-driven automation is expected to impact over 30% of existing jobs, with data analytics and business intelligence roles seeing increased demand.

Here are a few:

• More automation: As AI gets smarter, we’ll see more automation in data analysis and reporting. AI Business Analysts will spend less time on manual tasks and more time on interpreting data and providing strategic insights.
• Cloud-based tools: Many companies are moving their data to the cloud, so tools like Hadoop and Tableau will need to adapt to work in cloud environments.
• AI-powered analytics tools: AI itself is getting smarter, so we’ll see new tools that can analyze data faster and more accurately.

Conclusion

Get to work on Power BI, Python, Tableau, Hadoop, and SAS and become more valuable to any company.

Start now and check out this link to get started with your AI Business Analyst journey!