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What Does A Business Intelligence Team Do?

Table of Contents

BI is a set of methods and tools designed to help organizations make better decisions using data, such as business analytics, data mining, data visualization, and data tools and infrastructure.

A business intelligence team uses various data warehouses and data lakes to consolidate data across operations to improve accessibility. Other tools such as embedded analytics and data visualization translate vast volumes of complex datasets into digestible dashboards, and reporting help contextualize the most important metrics.

This is so business users can make sense of the available connections, trends, and insights.

More importantly, the BI team is responsible for building and managing the data infrastructure that undergirds all self-service activities.

Some companies refer to a group like this as a data analytics team.

Self-service analytics doesn’t work well if the BI team is not a strong and coequal partner with the business.

Companies need to invest more, not less, in their BI teams for self-service to succeed.

What Does Business Intelligence Do?

Many people have heard of the term business intelligence, but may be unsure what it means.

Business intelligence refers to the insights gained from analyzing companies’ business information.

Business Intelligence (BI) enables companies to use the data they hold efficiently by analyzing it and then using it to inform business decisions.

The insights are for current and historical data.

It’s the process of surfacing and analyzing data in an organization to make informed business decisions.

It leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions.

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business.

Good BI tools let you generate and send out reports to stakeholders so they can monitor performance indicators at a high level.

A Framework of Business Intelligence

The general framework for business intelligence is best summarized as follows:

  1. The sourcing, organization, and consumption of business data through reporting systems

  2. The discovery, generation, and contextualization of insights through analysis solutions

  3. The business framework and process used to act on insights to meet strategic objectives

What Tools Does Business Intelligence Require?

In addition to data warehouses, dashboards, reports, data discovery tools, and cloud data services, BI tools include data warehouses. Your data can be analyzed using these tools.

Because of these requirements, BI professionals should know the business process improvement methodology, business analysis, some general economics, and coding in their application of choice.

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The Business Intelligence Team

Most organizations do have some form of analytics, using spreadsheets as an entry-level tool. It’s still common to find organizations that lack a formal analytics capability.

So, that’s an excellent reason to build a business intelligence team.

However, it is probably more common today to find that these functions — building reports, dashboards, and analytics — exist within an organization but are not well-defined and have some very informal functions.

In BI teams, project roles are combined with program roles to manage BI initiatives and the organization’s business intelligence efforts.

A business intelligence team includes a mix of project and program roles that cover specific BI initiatives and the overall management of an organization’s BI activities.

They are a corporate group that does data validation, designs and builds data and analytics applications, governs and manages data resources, and builds and manages the data environment and underlying infrastructure.

In large organizations, separate people handle each role.

Whether an organization is thinking about starting a BI team today or is already beginning to invest in architecture, tools, and people, the future of analytics depends on recognizing and rewarding the significant contribution it can make.

Even departments with lots of data analysts need the BI team to build certain types of applications for them.

Data analysts and even data scientists don’t get paid to design, test, build, and manage complex, high-performing, multi-user applications, nor do most have the skills or time to do so.

Business Intellect

Business intelligence (BI) collects, stores, and analyzes data, the technological and procedural infrastructure that allows a company to gather, store, and analyze data.

Data Stewards

A data steward oversees corporate governance, ethics, privacy, and security policies as they flow through the IT team to the BI team and business users.

This is a demanding task, but in the beginning, it may not be a full-time role.

Data Analysis

Analytics are the tools and processes exploring data, extracting performance, and drawing conclusions and insights to offer end-users the ‘why’ behind the metrics.

The types of analytics you can expect to perform are:

  • Writing data collection and processing procedures

  • Ensuring data is being correctly gathered, stored, and analyzed

  • Reporting data findings to management

  • Continually monitor data collection

  • Develop methodologies to improve data analysis

An organization may need to add new members with specific skills, such as machine learning, with both organizational and virtual teams.

They create effective models and representations of the business with the database or BI tools of choice.

Some of this modeling may already be within the IT infrastructure, especially if the organization has a data warehouse.

But even then, business intelligence teams often find they need to create models ad hoc for specific purposes, such as an experimental advertising campaign or a special project for executives.

That model probably does not exist within a data warehouse designed to provide an authoritative long-term business record.

This captures the relationships between data, the specialized calculations, and the hierarchies of data by geography, tax jurisdiction, sales region, product categories, etc.

Data modeling and statistics expertise is common ground for a data analyst.

Business intelligence analysts are increasingly valuable to companies as the amount of data they collect continues to grow.

Many predict the demand for business intelligence analysts to continue to rise in the future to meet the needs of companies and the data that they hold.

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Business Intelligence Administrator

This role monitors and manages BI systems, handling a variety of system maintenance, testing, performance tuning, and security tasks.

Additional duties include: 

  • Monitoring system performance, resource utilization, and optimizing systems

  • Troubleshooting system issues, and coordinating responses with IT and business managers

Who Uses Business Intelligence Tools?

Business intelligence tools can be used by all teams at a company, including sales, marketing, and customer support. Team members and executives can both make use of BI tools’ output.

These days, businesses rely on business intelligence software to identify and extract valuable insights from the massive amounts of data they accumulate.

Data engineers and data analysts can also use the convenience of a BI tool when performing their investigations.

Business Intelligence Vendors

They offer the quick and easy-to-digest data summaries at the heart of BI’s value proposition.

There are tons of vendors and offerings in the BI space, and wading through them can get overwhelming.

Some of the major players include:

  • A self-service analytics platform provides data visualization and can integrate with a range of data sources, including Microsoft Azure SQL Data Warehouse and Excel

  • A “guided analytics platform” capable of providing enterprise-grade business intelligence and data analytics, which blends analytics from a range of sources to simplify workflows

What Are Data Scientists?

A data scientist is typically involved in advanced analytics applications, such as machine learning, predictive analytics, and big data analytics.

But data scientists sometimes also work in conjunction with BI teams on analytics projects.

Business Intelligence Examples

Reporting is a central facet of business intelligence, and the dashboard is perhaps the archetypical BI tool.

Dashboards are hosted software applications that automatically pull together available data into charts and graphs that give a sense of the immediate state of the company.

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What Is Data Querying?

In addition to connecting to data sources, it is also worth checking how easily the BI tool can connect between data sources.

A good BI tool will make it easy to take queries from different data sources and join them into a new one.

Connecting and merging data from multiple data sources allows for additional insights that are not possible on their own.

Data Visualization

Data visualization is a core component of most business intelligence applications. A good chart can convey insights faster than a plain table of numbers.

When considering self-service BI tools, see what kinds of charts they have available and the amount of customization possible with them.

Visualizations compiled into dashboards can quickly tell a story and highlight trends or patterns that are not easily discoverable when manually analyzing the raw data.

This accessibility also enables more conversations around the data, leading to broader business impact.

Business Intelligence vs. Business Analytics

Business intelligence is descriptive, telling you what’s happening now and what happened in the past to get us to that state.

On the other hand, business analytics is an umbrella term for data analysis techniques that are — that is, they can tell you what’s going to happen in the future — and prescriptive — that is, they can tell you what you should be doing to create better outcomes.

The Difference Between Traditional Business Intelligence & Modern Business Intelligence

Historically, business intelligence tools are based on a traditional business intelligence model.

This was a top-down approach where the IT organization drove business intelligence, and most, if not all, static reports answered analytics questions.

Modern business intelligence tools analyze data quickly and are more interactive and agile.

Organizations typically use modern BI tools when business users need insight into quickly changing dynamics, such as marketing events, in which being fast is valued over getting the data 100% right.

Augmented Analytics

There’s a new trend emerging for business intelligence termed augmented analytics. It’s when machine learning meshes with software and guides users on their queries into the data.

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