Business Intelligence vs. Data Analytics: What's the Difference

Business Intelligence vs. Data Analytics: What's the Difference

Published on
August 5, 2022
Updated on
September 26, 2022
Author
Luan Campos
Reading Time
Considering the similarities and differences between BI and BA, which would you want to hire? For instance, do you need a data analyst for BI or BA?

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Consider a small mom-and-pop joint with a stall selling merchandise to passers-by. If they ever need to know if they were doing well as a business, they could check how much they're making and ask their customers how they felt about their goods and their service.

Larger organizations will need a bit more than that. They’re going to need massive amounts of data in comparison, as well as the tools and know-how to process all that data into useful insights.

These insights are what business intelligence and data analytics can offer.

Differences and Similarities in Business Intelligence and Data Analytics

Business intelligence (BI), simply put, is the process of mining valuable information about a business's current performance. Larger organizations contain many moving parts. There are teams and departments, overlapping and interconnected business processes, and sometimes even geographically distributed members for mid-sized companies. What BI does is surface and analyze information about the operation of a business and, through that, synthesize key points on company performance that arm decision-makers with actionable insight.

BI is often used in:

  • Increasing productivity and organizational efficiency
  • Improving employee satisfaction and lowering churn
  • Improving in-market competitive advantages
  • Improving customer experiences

BI is generally divided into data gathering, analysis, and reporting. Modern businesses almost always require BI to crunch big data, so an extra category for data storage has become increasingly integrated, as well. BI is also holistic, and it considers information from all parts of a business. Performance indicators across the board are brought together into a whole that's greater than the sum of its parts. It’s not a mass of raw figures anymore — rather, it's a bundle of key insights.

Data analytics, on the other hand, is the analysis of sets of data to draw conclusions that are meant for a specific context. While used interchangeably with business analytics (BA), data analytics is a broad term and the process itself can be used on practically any data set and in any context. It’s more appropriate to use BA instead of data analytics in a business context the same way it’s more appropriate to use BI instead of just “intelligence.”

BA is essentially a process for solving business problems through data analytics. It uses the statistical models and quantitative methods of data analytics and applies them to a business context. BA relies on the high quality and sufficient quantity of data and the right people and tools to analyze all of it.

There are a few types of BA:

  • Descriptive analytics that tracks KPIs to get a better understanding of the current state of the business (yes, this is practically the same functionality as BI)
  • Predictive analytics that, as the name implies, analyzes existing trend data to predict likely future scenarios
  • Prescriptive analytics, which is predictive analytics that comes with recommendations or prescriptions

Business Intelligence Vs. Business Analytics

Diagnostic and descriptive analyses are predominantly used in BI to analyze past and current performance. BA is usually leveraged for its predictive and prescriptive analyses. BI’s domain is the past and present, and BA’s domain is the present and future. They can and do work well together. Information collected via BI tools, for instance, can make excellent foundations for BA. BI data gathering can present BA experts with sufficient information so that they can zero in on specific areas for deeper BA use cases. BI and BA are used to guide organizational growth or transformative efforts, respectively.

Salary, Skills, and Roles

BI roles typically begin with a humble BI analyst position or equivalent. According to Glassdoor, the average salary for a BI Analyst in the U.S. is $85,690, with higher estimates being around $120,000 annually. Senior and lead analyst roles will naturally garner more wages.

The usual minimum skills and qualifications of a BI analyst include:

  • A degree in computer science, data science, business, or related field. A viable alternative is equivalent hands-on experience (which, for students, would be equivalent to internships or placement opportunities)
  • Additional certifications related to data analysis and database technologies and methodologies such as SQL, cloud computing, and data visualization, or equivalent and admissible practical experience

The specifics of the certifications/experience required depends on the company and position. The usual tasks of a BI analyst role include:

  • Analyzing data through a variety of analytics tools to determine business performance
  • Transforming raw data into reports, charts, and other easily understandable insights
  • Developing metrics for performance assessments and KPIs with guidance from stakeholders
  • Developing policies and procedures for data collection and analysis
  • Analyzing information related to the market and competitors
  • Using data analysis to help businesses determine priorities and define process pipelines

In the same vein, BA roles also typically start with BA analyst positions or equivalent. According to Glassdoor, the average salary for a BA Analyst in the U.S. is $86,324, with higher estimates exceeding $133,000 annually. Senior and lead analyst roles will naturally garner more wages.

The usual minimum skills and qualifications of a BA analyst include:

  • A degree in a management-related field and aptitude in statistics and math
  • Proven knowledge of data, data investigation, and analysis
  • A specialist qualification in data analysis and/or working knowledge in SQL databases and SAP
  • Collaboration skills in the context of interdepartmental communication and a good grasp of project management processes
  • Proven skills in presentation, spreadsheet data administration, and reporting

The specifics of the certifications/experience required depends on the company and position. The usual tasks of a BA analyst role include:

  • Examining and analyzing collected data and providing recommendations based on results
  • Develop improvements and/or solutions to business processes and/or issues
  • Develop a deep understanding of the company’s operations, market, and data
  • Perform significant amounts of research to improve the data analytics capabilities of the organization

Business Intelligence vs. Data Analytics: Typical Jobs and Careers

With both processes so closely related and similar, there are indeed some jobs that exist in both BI and BA. In both cases, roles progress from junior to senior based on the scale of their work’s impact on the business. Junior roles impact the organization on a tactical level, where the importance is largely localized to a specific team or process. Senior roles impact the organization on a strategic level, where the significance is spread across departments or deep into complex pipelines. The scale of their work’s impact directly correlates to the scope of their roles. The more strategic the impact, the more they may require teams or junior roles to support them.

Some starting positions that may either be in BI or BA include:

  • Data analysts — An entry-level role that gathers, processes, and evaluates data. Data analysts prepare insights they’ve extracted for reports and meetings, and thus they are heavily involved with the business side of data analysis. They often support roles like project managers who in turn need their data-related skills to make better-informed decisions on the projects for which they are responsible.
  • Data scientistsData scientists are more concerned with modeling the data gathered, and have become much more in demand after the boom in big data. Simply collecting and analyzing data may not be possible given the format and sources of raw data. Organizations typically need data scientists to create data models using technologies like machine learning so that the raw information is turned into something more useful.

As for some examples of typical jobs specific to BI:

  • BI Developer
  • ETL (Extract, Transform, Load) Developer
  • Data Mining, Data Modeling Specialist, and Data Visualization (three separate specialist roles for each stage of BI: data gathering, analysis, and reporting)
  • Knowledge Management Developer or Database/Datawarehourse Expert (a specialist in the data storage aspect)
  • SAP Business Intelligence Specialist, Power BI Developer, or Tableau Developer (platform or tool-specific specialists)

Some examples of typical jobs specific to BA include:

  • Data Architect
  • Chief Data Officer (or other leadership roles specifically pertaining to data)
  • Market Research Analyst (specific process-aligned position, i.e. markets)
  • Statistician (or similar roles that are method-specific subject matter experts)
  • Information Security Analyst (partially cross-disciplinary role, i.e. cybersecurity, which may need additional requirements or experience)

Who is Best to Hire for Your Company

Considering the similarities and differences between BI and BA, which would you want to hire? For instance, do you need a data analyst for BI or BA?

You can look at this conundrum another way: between BI and BA, what do you require the most in your organization right now? BI is usually more optimal for larger operations, while BA’s future-thinking approach applies to every business, with a caveat: restrictions imposed by data. You might think you benefit from BA, but unless you have sufficient data and the right tools or expertise for its analysis, you won’t be able to reap BA’s rewards.

BA typically uses more advanced tools and methodologies because of the statistical and analytical processes involved. That on top of the data restrictions generally prevent smaller-scale organizations from benefiting widely from BA. BI and its descriptive analysis of existing information can still identify bottlenecks in historical performance and present insightful perspectives on current operations, though without the diagnostic and predictive modeling of BA.

In terms of use cases, there are also some factors to consider. A comprehensive BI process or system generates visualizations and reports for every facet of a business, and there exists a slew of self-service BI tools that can enable non-technical users within a company to contribute to their BI processes. BA, by and large, requires a bit more advanced and technical knowledge to operate.

Again, from the perspective of use cases, BA can better inform decisions about how to change products or operations while BI provides insights that can optimize processes. This is why BI is used to guide business growth, while BA can help identify key points to support transformative efforts.

Business intelligence can be applied to practically any size of business, from fast-growing startups that need to understand their processes better to optimize processes and soothe growing pains, to enterprise-level organizations that need to streamline interdepartmental performance.

BA is more valuable for businesses who want to pivot their model or break into new markets, where the predictive and prescriptive capabilities will be useful for forecasting performance. That said, again, the quality and quantity of data as well as the tools used and the skills of the people in BA roles will determine how accurate BA predictions will be.

So what do these differences look like in action? Let’s take a look at three specific cases and how BI and BA would work within them: enterprise reporting, performance management, and inventory management.

BI and BA in Enterprise Reporting

BI in enterprise reporting: Typically, BI can be used to generate reports related to staffing and productivity, business expenses, and sales and revenues, among others. BI can also be used to create interactive visualizations that present the relationships between these different parts of business.

BA in enterprise reporting: Typically, BA is used to analyze historical performance to predict future trends to guide strategic planning. BA supports key decision-makers by identifying how KPIs and other crucial metrics will hold in the future.

BI and BA in Performance Management

BI in performance management: BI is typically used in tracking employee workloads, identifying productivity trends, and seeing how historical performance impacts company goals.

BA in performance management: BA is usually reserved for closely monitoring how project objectives align with what resources are available at hand. For example, BA can identify reasons for employee churn and recommend changes through prescriptive analysis to recruitment pipelines and project milestones so as to address the issue. BA can help propose employee enablement measures and benchmarks as well.

BI and BA in Inventory Management

BI in inventory management: BI tools used in inventory management can work on pre-built reporting templates to make it easier for non-technical team members involved in the pipeline to understand and present stock details and inventory concerns. BI can keep all key members of an inventory pipeline on the same page even if they’re non-technical.

BA in inventory management: BA is more useful in predicting and managing supply and demand through methods like materials requirement planning and Just-In-Time management. BA can help streamline reordering via qualitative analysis of inventory and trend forecasting tools. BA can help decision-makers shape inventory management strategies and also point out potential key supplier partnerships.

Ready to Hire People for Business Intelligence or Business Analytics?

If you’re still uncertain, Revelo can help clarify your needs and recruit the right people for the job. As a talent marketplace, Revelo can support your hunt for qualified and experienced people in business intelligence and business analytics by finding and hiring tech talent. We make the effort simple and cost-effective by matching you with pre-vetted tech talent in a matter of days.

Contact us and get matched with vetted talent within three days.

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Full-Stack developer with 6 years of experience working with MERN stack. Worked for multiple transnational companies focused on web and cloud, technology services, and R&D. Major professional experience in Frontend with Javascript, Node.js, React.js, and Vue.js

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