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What Is The First Step In Business Intelligence?

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The first step in business intelligence is collecting a large amount of data or gathering data from their business operations. But a business should introduce business intelligence to its team beforehand.

As business analytics tools become more powerful and affordable than ever before, more and more business leaders are building upon their existing technology toolsets to add accurate business intelligence (BI) to their organization’s capabilities.

Maybe you implemented a business intelligence solution that meets your needs for keeping your data organized, but you don’t know if you’re getting the desired results.

Or maybe different departments have different solutions, and it’s time to rethink how you use business intelligence.

If you see inefficiencies in the way you use business intelligence, feel like you don’t have seamless access to data, or tire of the headache of not knowing which set of data to believe.

It’s time to revamp your strategic goals.

Implementing a new business intelligence solution in a truly transformational way is no small feat. 

Still, with an effective strategy, you can maintain accountability for your timeline and objectives and get more done for your company with business intelligence.

My name is Brandon-Poplstein, the chief operating officer at Kennected.

This blog will discuss the steps of bringing business intelligence into your existing corporate infrastructure.

You will learn to set up a business intelligence strategy and integrate tools into your company workflow.

What Is Business Intelligence?

Business intelligence tools have been around for more than 20 years. However, the look and basic functionality of a “standard” BI tool have changed a lot.

Instead of just static reporting, each vendor now offers ad hoc reporting or interactive dashboards for analysts to collaborate on.

Businesses define business intelligence in many ways.

By the earliest definition (1958), business intelligence is “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

A broader and perhaps more current definition of this discipline is this: business intelligence is collecting business data and turning it into meaningful and actionable information towards a strategic goal.

A business intelligence strategy allows an organization to derive maximum value from all its data.

End users and corporate executives can make more informed business decisions with actionable information.

Business intelligence aims to create more efficient operations by improving decision-making and streamlining processes by business managers and other end users.

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What Tools Makeup A Business Intelligence Strategy?

BI encompasses a variety of tools, applications, and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards, and data visualizations to make the analytical results available to corporate decision-makers as well as operational workers.

Most often, the infrastructure includes the following technologies that cover data storing, processing, and reporting:

  • Data sources

  • ETL (Extract, Transform, Load) or data integration tools

  • Data warehouse

  • Online analytical processing cubes

  • Data marts

  • Reporting (BI) tools

As you consider your overall approach toward gathering and organizing the data for your BI initiative, you’ll need to determine how you can best harmonize and consolidate the information and make it available to the users who will rely on your business intelligence systems for meaningful insights.

How Are Business Intelligence Systems Implemented?

BI is basically about slicing and dicing data iteratively to identify patterns that marketers can use to make informed business decisions.

Your company can thus optimize its business plan and gain competitive advantages even from unexpected sources, thus improving its bottom line.

Most BI projects fail not because of faulty technical implementation, but because of a lack of a strategic focus.

Business intelligence should be a lever that enables a company to “lift” itself more efficiently towards its strategic goals.

When leaders face “what if” scenarios, BI helps them understand their options and narrow down their choices using a data-driven approach.

This is especially valuable when BI tools are available across a broad base of users within the organization.

Once implemented, the BI systems will automate several processes, analyze the available data, and generate reports, among other things, helping a great deal in improving the efficiency of your business by enabling the authorities to make informed decisions.

What Is The BI Framework?

As its name implies, business intelligence frameworks connect the various elements of a business, such as organizational roles, key performance indicators, authorizations, and visualizations.

Business intelligence plans can be implemented more quickly and easily in this way.

There are various structural elements of a BI architecture you will have to develop if you want to create a custom solution for your business.

In other cases, you are always free to choose a vendor from the market that would carry implementation and data structuring for you.

In addition to data integration, the framework entails new analytical structures for the data warehouse, new views, universes, and cubes within the BI tool suite, a brand new BI tool, education for end-users, tool training for end-users, and change management.

A successful BI and analytics strategy combines a data-driven and objective knowledge of markets, customers, operational processes, business performance, and better-informed insights from the BI team and business users.

How Data Literate Are Your Employees?

Consider the data literacy level of your employees. How simple or complex should their dashboards be?

Managers may need to understand high volumes of data before making the necessary decisions.

Do they need an extremely interactive tool with drill-down capabilities, or will employees or executives need to only quickly check the status of key metrics and move on?

It’s time to start talking about the technical details of your business intelligence strategy.

All of this will affect which solution you choose. Be sure to consider how the data visualization tool will coordinate with the long-term objectives within your strategy, not just the short-term.

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Choose Your BI Platform

To use your existing data to its fullest potential, you need to start by selecting a BI platform.

Nowadays, many different types of business intelligence platforms are available, but most companies choose one based on their needs and the available budget.

Data Collection

Your BI solution should provide you with the information that can help you achieve your desired business outcomes, those things that will make the most difference to your organization.

You can get the most from your BI tool when you understand what you want your raw data to reveal.

Source data is obtained, cleaned, indexed, associated, and cataloged during the data acquisition process.

Data becomes information after it’s processed to add context, relevance, and purpose. Most companies collect a large amount of data from their business operations.

Once extracted, the ETL tool starts data processing.

The ability to analyze and act on data is increasingly important to businesses. Modern BI tools allow organizations to evaluate data from multiple sources.

Using polls and surveys amongst decision-makers and other business users allows you to learn more about how they use data.

How many meetings and decisions already rely on data, reports, and dashboards? Which of the existing reports are the most useful?

Knowing where you stand allows you to take further first steps toward a BI strategy.

Once you have defined what is most important to your role, department, or business, you can use your BI tool to provide the intelligence needed to move forward.

OLAP Cubes Architecture

A warehouse and OLAP are used in conjunction, as cubes store relatively small data and provide processing convenience.

The data warehouse + OLAP cubes architecture can be considered a typical one.

Companies use it that require data storage and complex multidimensional analysis of the information.

Consider an OLAP architectural approach if you don’t want to bombard your warehouse with queries.

OLAP cubes define specific data dimensions for querying data and reducing the load on the main warehouse.

Assemble Your BI Team

Once you have selected a BI platform, start assembling a team of experts to build and maintain your business intelligence system.

Find someone with the skills needed to install, configure, and support a BI toolset in your organization.

Also include a data analyst on the team, as this person will be responsible for unlocking the full value of your company’s data.

Setting Goals

So, your business intelligence tool is in place. Relevant data starts to flow from your ERP and external data sources into the central database.

The next critical process for successful business intelligence data is setting your goals for analysis. Being able to make business decisions based on data is a competitive advantage.

To have any chance of success with business intelligence, the business must first define what success looks like, which can be a problem.

At the start of this process, business users often don’t know what they want because they haven’t had adequate access to data and may lack a clear idea of what’s possible.

A business intelligence strategy will involve technology, and the focus needs to be on how that technology will serve your overarching business goals. Technology always serves a purpose.

With your team of key stakeholders, discuss and prioritize the business goals that you would like to spur on with your business intelligence strategy, and then outline how business intelligence will support each goal.

Don’t limit yourself in this stage.

Build A Data-Centered Culture

Ensure that everyone in your company understands the necessity of data-driven decision-making.

The change will take time, and it won’t be easy, but you can gradually foster a data-driven culture by encouraging everyone to learn how to use BI tools and visualizations.

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Engage With Stakeholders

The final, critical ingredient for business intelligence success is to engage all stakeholders in an ongoing effort to govern and manage master data and metadata that feeds the data warehouse or alternative data solution.

Ensure you provide decision-makers with easy access to reliable, meaningful information.

Companies that embrace this step and dedicate the necessary resources are rewarded with a competitive advantage when everyone in the company has the information they need to optimize their portion of the business.

Measure & Monitor KPIs

Alongside this ad hoc analysis, you’ll want to leverage your BI systems to measure and monitor the key performance indicators (KPIs) that align with your organization’s strategic objectives.

Business intelligence differs from traditional approaches to financial reporting in its focus.

Rather than focusing on short-term operational matters, BI focuses on the data at a higher level.

Data Governance

Invariably, every business intelligence project shines a spotlight on the organization’s data quality.

Issues may exist if business processes don’t enforce data quality, or anytime various systems treat customer or product information differently.

Descriptive Analytics

One of the biggest errors is using business intelligence and predictive analytics terms interchangeably.

Business intelligence is a data analytical approach, answering the question: What was happening? This type of data processing is also called descriptive analytics.

With the help of descriptive analytics, businesses can study the market conditions of their industry and their internal processes.

What Are Business Performance Management Tools?

Businesses use these to track and assess progress toward company objectives.

Predictive Analysis

This is a branch of data mining. It attempts to predict possibilities and trends.

What Is A Data Warehouse?

A data warehouse collects and organizes company data from various sources into a single, easily accessible location.

Business analytics or data management tools mine and analyze the data warehouse.

BI usually involves, not real-time data, but aggregated or summarized data that may have been loaded into a data warehouse and transformed for analysis.

This distinction means that the data used in BI does not necessarily have a direct connection to source systems because it doesn’t need one. Business intelligence facilitates exploration.

BI makes it easy to perform ad hoc inquiries, and often prompts users to ask new questions they had never before considered.

The User Interface

A user interface is an interactive dashboard with data visualization reporting capabilities to provide quick access to information.

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Data Visualization

For years companies have been buying reporting software, such as Cognos or Business Objects, hoping to solve their reporting challenges with a single purchase.

Today, companies buy newer tools like Power BI and Tableau with similar expectations.

While these tools alone can’t easily solve the age-old problem of “garbage in, garbage out,” they play a critical role as the user interface once the data is prepared and report-ready.

We leverage one or more reporting applications (based on specific requirements) to effectively communicate the data’s story and reveal important insights.

Be sure to consider how the data visualization tool will coordinate with the long-term objectives within your strategy, not just the short-term.

Ideally, a data visualization tool or any business intelligence solution should have immediate and long-term benefits.

Hop-On The Kennected Train

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