Value Of Business Intelligence Software

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Value Of Business Intelligence Software – Introduce new offers to adapt to the current market situation? Successfully track KPIs by getting notifications? And even get comprehensive answers to all your complicated questions about your business? Then you might benefit from looking at business intelligence capabilities.

Companies in most sectors and industries strive to facilitate decision-making, drive innovation, reduce costs and improve quality. Today, companies can achieve these goals by harnessing the power of analytics, which has largely evolved due to the explosive growth of business data and technological advancements.

Value Of Business Intelligence Software

Broadly speaking, business intelligence (BI) refers to an information system that transforms data into knowledge with the intention of providing analytical information to users. A broader definition states that “Business Intelligence is an umbrella term that includes applications, infrastructure, tools, and best practices that enable access and analysis of information to improve and optimize decisions and performance,” according to the Gartner IT Glossary.

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It is necessary to understand that the main goal of business intelligence is to find out what the company can get from the data. BI goes beyond data collection to include business processes and data analysis procedures.

Understanding more about the technology is worthwhile as it would help you understand the benefits that BI introduction could bring to your company and how it can find its place in your business.

Therefore, let’s examine the key components of BI. A BI system that we can freely divide into three parts: data sources, data warehouse and OLAP cubes and analytical findings.

Data is an integral part of BI in particular and analytics in general. Modern companies deal with a large number of electronic documents, spreadsheets, invoicing, orders and other documents. In order to collect, store, use and disseminate this information, companies use data organization systems, such as:

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Operational applications are accessed to perform regular operations of the organization. They allow us to enter and retrieve large amounts of specific information, such as company legal data, financial data, personal employee data (HRM systems), sales and customer data (CRM systems) and many others.

Operating systems typically use databases for online transaction processing (OLTP). Common examples of applications running on OLTP databases are: order entry systems, inventory management systems, banking systems that perform money transfer operations, retail, etc. Such databases help support fast processing of small workloads and transactions.

It is worth understanding that the primary function of an OLTP database is to support day-to-day operations, not to perform complex analysis. You will be able to quickly identify the status of a customer’s order, but it will take a lot of time and effort to determine how many of your customers who bought your item 3 months ago are repeat buyers. OLTP databases are not for long queries, so they are not able to provide the sufficient level of analysis that a company needs. For this, they can serve as sources for data storage.

After we securely collect and store operational data, we need to analyze it before it can be used to support decision-making activities. So, the Extract Transform and Load (ETL) process delivers the data to the next stage, that is, the data warehouse.

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There is a need to integrate data from different data sources and to optimize and dedicate the analytics layer. A data warehouse (DW) is exactly the solution that meets these needs – it is a database that stores data in a single format and enables easy analysis. DV is a core component of BI.

Data warehouse modeling most often supports online analytical processing (OLAP), which encompasses the larger category of business intelligence. DV can serve as material for multidimensional datasets known as OLAP cubes. They enable managers to gain insight into information through fast, consistent and interactive access to it. Many OLAP applications include business process management, sales reporting, marketing, forecasting, financial reporting, and more.

Additionally, a department within an organization can take advantage of using a simple form of data storage called a database. The database is focused on one topic or functional area, which can be production, finance, sales, marketing or any other.

The instrumental goal of BI software is to provide users with meaningful, actionable information. Analytical findings come in one or a combination of forms: reports, dashboards, visualizations, charts, graphs, etc. In fact, one of the hallmarks of a BI program is the rich visualization of the resulting reports.

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It follows that creating a solid business intelligence solution to support your business goals requires a highly skilled team of dedicated professionals with the right competencies.

The introduction of BI tools into the company’s daily operations leads to accelerated decision-making, increased operational efficiency and reduced costs. The resulting benefits are also determined by the set of problems the software is designed to solve. For example, spotting business issues that need improvement, identifying good opportunities to cross-sell your merchandise, and so on.

The practice of using data to make better business decisions can be described not only by the term Business Intelligence, because business analytics generally has the same meaning. However, these are not the same things and it is worth knowing the difference.

Business intelligence entails descriptive and diagnostic analytics, while business analytics helps to invoke predictive and prescriptive analytics.

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Both involve the collection and analysis of data, and both share the same goal of increasing a company’s efficiency through the use of data analysis, although the two perform different functions in business.

BI describes the past or current state of business; it’s all about extracting insights from the data that will tell you what happened, why it happened, and what’s happening now. With its powerful reporting and data analysis mechanisms, BI is able to optimize and streamline ongoing operations.

The next step in analytics is business analytics, or in other words advanced analytics. It goes beyond telling what happened or is happening. Business analytics deals with predicting future developments based on all past and present data. The specific intent of BA is to prepare the business for the upcoming challenges. By predicting and identifying problems before they happen (Predictive) or by suggesting certain proactive actions (Prescriptive).

After such a comparison, implementing business analytics software might be a more attractive solution. So here comes the logical question…

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Should companies adopt BI when there is a more likely opportunity to achieve proactive advice from business analytics?

Things are not that simple. To predict the future, you still need to know what and why certain actions happened in the past and what and why is happening now. Advanced Many companies can apply analytics on top of their BI solutions. We can say that business intelligence is the first step in the adoption of analytics that cannot be dismissed.

This means that the value of business intelligence is quite high as never before. Such software is sufficient for those who want to understand their work processes and improve decision-making. Then, with these insights, improve your business from the ground up.

If you are interested in developing a custom solution — send us a message and we will schedule a conversation about it. Today’s data-driven world requires people and organizations to be data-savvy to make decisions and create value—but it can seem difficult to differentiate products.

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BI platforms are built around providing standardized, operational reporting, with an emphasis on distributing data in a repeatable manner. Many modern BI tools still adhere to this model. Visual dashboards improve the end user’s ability to understand information, and charting software reduces the time it takes BI consultants to create dashboards – but they are not enough to enable users to adopt analytics as part of their decision-making process.

If you want to create value with your data strategy, you should embrace modern analytics. New revenue streams, cost savings and efficiencies add value to the organization rather than fixed expenses. The value for companies that build their culture based on insights generated from real, verifiable facts goes beyond the cost savings realized by organizations that deliver report- and dashboard-based solutions.

Understanding the value of business intelligence should be assessed not only in terms of the cost and functional benefits of the software, but also in terms of the business benefits enabled by data-driven decision making.

Depending on where your organization is on its journey to becoming data-driven, you may choose to focus on cost optimization, efficiency or effectiveness.

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Compare the gains in worker productivity achieved by different solutions and use the cost of labor to calculate the return on your investment.

Users often estimate license costs, but don’t consider support, training, and additional technologies that add to their overall cost. This model assumes that the gross value you’ll get from the many BI technologies available to you will be roughly the same, meaning it’s most important to choose the option that will cost you the least money. This is not always true, but it works in some situations.

There are several factors that should be factored into the total cost of ownership, not just the cost of the license. These include platform and labor costs:

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