Understanding Business Analytics and the Tools Used

“Big Data is the key to success” is a common refrain across many sectors of the modern economy. However, most businesses are not yet seeing the tangible benefits promised by the heralds of the “data-driven future” and struggle to turn their data into real benefits. They end up with tons of information and raw data but can't make sense of it or use it to improve their business.

That's where business analytics and data analysis tools come in, turning raw numbers into useful insights that guide your decisions. It’s like having a treasure map that shows you where the insights are hidden in your mountain of raw data. By learning about business analytics, companies can:

• Make smarter business decisions based on consumer intelligence, market intelligence, a deeper understanding of your market landscape and more
• Get ahead of their competitors
• Work more efficiently
• More effectively reach, and retain, customers

Read on to explore how business analytics can transform your data from an overwhelming challenge into a powerful asset for your company's growth and success.

What Is Business Analytics?

Business analytics is the process of collecting, organizing, analyzing, and interpreting data to gain insights and make data-driven business decisions. The world of business analytics is booming. In 2022, the market hit $274.3 billion, and it's still growing fast. Why? Because more and more company leaders realize how important it is to use data more effectively when making decisions. In fact, 98% of executives think they need to rely more on data analysis in the future.

But business analytics isn't just about understanding what's happening now. It can also help you:

• Figure out what's driving complex markets
• Predict future changes in the market and consumer tastes
• Spot opportunities before competitors do
• Reduce risks for your business

Quid Connect, for instance, acts as a central nervous system for your data, allowing real-time integration of insights from various sources, including both public data, like social media intelligence, and your internal business data. This enables decision-makers across your organization to access up-to-the-minute information, fostering more agile and informed choices. Meanwhile, Quid Predict leverages advanced AI to sift through vast amounts of historical data, identifying emerging trends that might escape human analysis. This foresight can give your business a significant competitive edge, allowing you to anticipate market shifts before they become apparent to others.

Key Concepts In Business Analytics

Business analytics isn't just one tool, it's a whole toolbox filled with different data analysis solutions for different jobs. Here’s a breakdown: 

• Descriptive Analytics

• Descriptive analytics involves analyzing historical data to “describe” what happened in the past. Creating descriptive reports requires data aggregation, mining, and visualization in order to provide a clear picture of past performance. 
• Think of it as your organization’s history book

• Diagnostic Analytics

• If descriptive analytics seeks to define “what” happened, diagnostic analytics is all about finding the data to answer the “why.” Using data discovery, correlation identification, and root cause analysis, organizations use diagnostic analytics to understand the driving factors behind both successes and failures. 
• Think of it as a forensic business detective

• Predictive Analytics

• Predictive analytics extrapolates trends in historical data to make predictions about future outcomes. Predictive analytics tools use statistical models and machine learning algorithms to process past data to find patterns and relationships between variables. These patterns can then be used to create forecasting reports. 
• Think of it as your company’s crystal ball

• Prescriptive Analytics

• Prescriptive analytics provides insights into what actions organizations should take based on predicted outcomes. Using simulation and decision analysis techniques, prescriptive analytics is about finding the best path of action by comparing the effects different strategies have on potential outcomes. 
• Think of it as a wise counselor for your business decisions

Each type of analytics builds on the others, giving you a fuller picture of your business. By using all of them, you can understand your past, make sense of your present, and plan for your future.

The Business Analytics Process

Whatever type of analytics process a business chooses to apply, it must follow a standard procedure in order to collect, analyze, and convert data into action. This process has six steps: 

• Problem Identification

The business analytics process always begins with the identification of a core business need. This is a problem or a question that needs to be answered. For example, a retail company may notice declining sales despite increasing foot traffic. The business then decides to apply business analytics insights to find ways to increase revenue. 

• Data Collection

The next step is data collection. It’s important to collect all relevant data from both internal databases and external sources. In the retail store example, this would include transaction records, customer demographics, consumer buying information, consumer sentiment towards your brand, and social media data. This data helps you find what products are most and least popular to help inform inventory. It’s critical to note that manual data collection is virtually impossible due to the large data sets required. This is why many firms turn to advanced solutions, like Quid, for assistance.  

• Data Preparation

Insights generated from business analytics are only as good as the data they use. It’s crucial to clean the collected data by removing duplicates, handling missing values, and standardizing formats. Next, the data must be consolidated into a central data warehouse for seamless analysis. 

• Data Analysis

Using statistical data analysis tools and machine learning algorithms, the next step is to analyze the data to uncover patterns and identify correlations. This is where data science knowledge is handy to have. It’s important to apply the right analytical techniques based on the type of problem. This includes statistical analysis, data mining, machine learning, and more. For instance, our retail company might use clustering techniques to reveal distinct customer segments with unique purchasing habits. 

• Data Visualization & Reporting

Once the data has been analyzed, the results need to be presented as easily digestible insights in the form of charts, graphs, and dashboards. Using these reports and visualizations, analysts can communicate their findings to stakeholders. In the case of the retail company, analysts might highlight key findings such as peak purchasing times and popular product combinations. 

• Implementation & Monitoring

The final step of the business analytics process is to convert insights into action and monitor the results. For example, the retail company might implement targeted marketing campaigns based on the identified customer segments and their product preferences. Analysts would then monitor the results by tracking sales data and making ongoing adjustments as needed.  

Here's a simple table to summarize:

What Are the Top Business Analytics Tools?

There is no shortage of well-known data analytics tools. You will no doubt have come into contact with many of these different platforms throughout your career. But let’s take a look at them in the context of business analytics and explore the strengths and limitations of each tool. 

• Microsoft Excel

• Microsoft Excel is a spreadsheet tool with data analysis and visualization capabilities. 
• Pros: Easy to use, versatile feature set, customizable dashboards and charts
• Cons: Struggles to handle large data sets, inadequate for complex data analysis, also hard to gather insights, as they need to be manually pulled

• SQL

• SQL is a query language for relational database analytics, providing a strong feature set and high levels of hands-on control over databases and how data is managed, manipulated and secured.  
• Pros: High level of control, widely used across many different databases
• Cons: Requires technical expertise to set up and maintain, does not offer any visualization, requires significant manual effort

• Tableau

• Tableau is a powerful data visualization and business intelligence platform. 
• Pros: Interactive dashboards, strong exploratory data analysis features
• Cons: Difficult to use, steep learning curve, more expensive than competitors

• Python

• Python is a versatile programming language with extensive libraries for data analysis. 
• Pros: Widely used for statistical computing, machine learning, and data visualization
• Cons: Requires programming skills and significant manual effort

• R

• R is an open-source statistical programming language designed to support data visualization. 
• Pros: Extensive capabilities for statistical analysis and predictive modeling
• Cons: Steeper learning curve than other programming languages, limited data manipulation capabilities

• Power BI

• Power BI is Misrosoft’s business intelligence and data visualization tool that helps companies analyze data and create interactive insights. 
• Pros: Combines data from several sources, capable of producing appealing reports and dashboards, integrates with other Microsoft products for end-to-end analytics
• Cons: Lack of customization, difficult to set up without technical expertise

• SAS

• SAS stands for Statistical Analysis System and is a software suite that allows users to perform statistical analysis offering advanced analytics, data mining, and predictive modeling capabilities. 
• Pros: Widely used by large enterprises, strong feature set
• Cons: Prohibitively expensive for many organizations, steep learning curve

• Qlik Sense

• Qlik Sense is a powerful business intelligence and data visualization platform that uses an associative engine for interactive, self-service exploratory analysis.
• Pros: Rich visualizations, advanced analytics integration, embedded analytics
• Cons: Can be resource intensive due to in-memory processing, may require technical expertise to use

• Quid Connect

• Quid Connect is an integration solution for passing insights and data from the Quid environment to other business intelligence systems, supporting them with real-time data. 
• Pros: Allows Quid data to be integrated with data from other sources, expands how Quid insights can be incorporated into decision-making across an organization, supports more comprehensive analysis
• Cons: If you don’t have other systems to integrate, you won’t have anywhere to export Quid insights.

• Quid Predict

• • Quid Predict is an artificial intelligence data analytics tool that detects emerging trends and themes from millions of data points. 
  • Pros: Weighs the relevance of trends and themes and forecasts their importance in real-time, uses generative AI to make predictions, enables organizations to proactively capitalize on emerging opportunities
  • Cons: A large number of features, which can be overwhelming to new users. However, this is counteracted by an easy-to-learn interface. 

Getting Started with Business Analytics

For smaller organizations or those looking to get started with business analytics, there are a few things to keep in mind. It’s important to identify what skills are needed to meet your analytics goals. These might include statistics, programming, and data visualization skills—see the following section for more detailed information. You’ll then need to provide employees with training resources to develop these skills and ensure that they know how to get the most out of business analytics tools. Here's a simple guide to help you get going:

• Identify Key Skills

  • First, figure out what skills your team needs. 

• Invest in Training

  • Once you have identified what specific know-how is needed:
  • Provide training resources for your team
  • Ensure everyone understands how to use your chosen data analytics tools effectively

• Start Small and Stay Focused

  • Big data can be overwhelming, so:
  • Begin with a small, manageable project
  • Set clear, achievable goals
  • Get your leadership team on board with the plan

• Consider Partnering Up

  • To kickstart your efforts:
  • Look into partnering with experienced providers like Quid
  • They can guide you through the process and help you avoid common pitfalls

As you grow more comfortable, you can expand your analytics efforts. The key is to start, learn, and improve over time. With patience and persistence, you'll soon be making data-driven decisions that boost your business.

Partnering with experienced providers like Quid can significantly smooth your entry into business analytics. Quid's user-friendly interface and intuitive design make it accessible even for teams new to advanced analytics, while its powerful capabilities ensure you won't outgrow the platform as your analytics needs evolve.

Skills Needed for Business Analytics

Getting the most out of business analytics isn't just about having the right data analytics tools. It's also about having a team with the right mix of skills. Let's look at the key abilities your team needs to succeed:

Technical Skills

Legacy non-automated, non AI business analytics platforms require technical expertise in a variety of forms, including:

• Coding languages like Python, R, and SQL
• Statistics and mathematical modeling
• Data visualization and reporting
• Familiarity with analytics tools and platforms

Business and Soft Skills

Equally important are the "soft skills":

• Strong analytical and problem-solving abilities
• Understanding of business operations and strategies
• Effective communication and storytelling with data
• Collaboration and teamwork skills

Continuous Learning

The world of data analytics is always changing. Your team needs to: 

• • Stay curious and eager to learn
  • Keep up with new tools and methods
  • Adapt to changes in the field

While developing these skills in-house is valuable, tools like Quid are designed to bridge the gap between technical complexity and business usability. Quid's AI-powered analytics can handle much of the heavy lifting, allowing your team to focus on interpreting and acting on insights rather than getting bogged down in technical details.

Business Analytics Use Cases and Applications

Business analytics isn't just for one department - it can help your whole organization thrive. Let's explore how it works in four key areas:

• Marketing Analytics

Marketing data analytics involves analyzing customer data to optimize targeting, personalization, and campaign performance. By leveraging data, businesses can identify customer preferences and behavior patterns, allowing them to tailor marketing efforts to specific segments. This leads to more effective campaigns, higher conversion rates, and improved customer satisfaction. 

• Financial Analytics

Financial analytics focuses on identifying trends, risks, and opportunities to drive financial planning and decision-making. Financial data can support forecasting, risk assessment, and the identification of cost-saving opportunities. Taking an analytical approach ensures that you have the information you need to create accurate budgets, optimize investment strategies, and ensure financial stability.

• Operations Analytics

Business analytics can also be applied to your core business processes. Operations analytics aims to optimize the way you do business on a daily basis, streamlining tasks, optimizing supply chains, and improving resource allocation for efficiency and cost reduction. 

• Human Resources Analytics

Your people are your most valuable resource. With human resources analytics, you can develop strategies to improve employee engagement and retention based on real employee data like performance, satisfaction, and turnover. With the power of analytics, you can create a more motivated and productive workforce. 

Here's a quick comparison of how analytics helps in each area:

Unlock Your Data's Potential With The Power of Quid

Most modern businesses are data-rich but insight poor. On average, organizations have up to 400 different data sources, with mid-sized and larger enterprises having far more. But success belongs to those who can turn that information into action. 

Business analytics is your key to unlocking this potential. It's not just about understanding what happened in the past; it's about shaping your future. By mastering business analytics, you're equipped to:

• Make decisions backed by solid data
• Spot opportunities before your competitors
• Navigate challenges with confidence

Companies that embrace analytics today will be the leaders of tomorrow. Don't risk being left behind as competitors race ahead with superior insights.

But how do you harness business analytics effectively? This is where Quid's innovative solutions come into play:

• Quid Connect: Your Data Integration Powerhouse
  • Seamlessly combines data from various sources
  • Provides real-time insights across your organization
  • Enables comprehensive analysis for better decision-making
• Quid Predict: Your Crystal Ball for Business Trends
  • Uses AI to detect emerging trends from vast data sets
  • Forecasts the importance of trends in real-time
  • Helps you capitalize on opportunities before they become obvious

Together, these tools let you transform raw data into a strategic asset. Enjoy having a bird's-eye view of your entire business landscape, with the ability to zoom in on crucial details at will. That's the power Quid puts at your fingertips.

Ready to see how Quid can revolutionize your approach to data? Take the first step towards a more insightful, competitive, and successful future for your business by booking a free demo today.