Company Business Intelligence – Business Intelligence (BI) refers to the ways in which organizations collect, analyze and use their business data. We’ve put together this infographic of business intelligence metrics to show you what they’re worth to businesses today.
Big data – a term used to describe the vast amounts of data that modern organizations deal with – has completely changed the way companies manage their operations.
Company Business Intelligence
Digitally mature companies are now expected to have a firm grip on their data to grow their services and remain competitive; and this is often achieved by introducing cloud solutions to utilize data that already exists in the company – unused.
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Of companies using the cloud, 87% of them report growth in their cloud. 41% of companies are able to directly attribute business growth to their use of cloud services.
Business intelligence means using digital tools to mine that data and turn it into something useful for decision makers to use – whether it’s responding more effectively to customers or reassessing an inefficient inventory plan; the ways data can be used by SMBs are virtually endless.
Despite its uses, many SMBs still lag behind leaders in digital transformation. About a third of organizations describe themselves as “data-driven,” leaving plenty of room for adoption.
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We created this infographic to demonstrate the value of business intelligence for companies that are still on the cusp of adopting new technology.
Advanced technological solutions such as business intelligence help companies gain and maintain a competitive advantage. By using modern tools that analyze your data, you can increase productivity, reduce unnecessary costs and uncover new ideas for your offers. For more information on cloud technology solutions and how they can help your SMB, download our free e-book, Which Cloud Option is Right for Your Business?
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Blog Post December 27, 2022 Who Really Needs an Advanced Cyber Security Strategy? Does your company need a unique cybersecurity strategy or can […] Cybersecurity Business Intelligence (BI) and Data Science (DS) are such hot buzzwords these days! But do you still use them interchangeably, like so many others? If the answer is yes, then it’s time to stop and reevaluate the way you understand these terms in the first place.
Because although BI and DS overlap to a certain extent, there are still significant differences between them. Just as there is a difference between making everyday decisions and future plans, or exploring data and describing it.
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So let’s go back to the basics and see what business intelligence and data science is all about.
Business intelligence is an umbrella term that covers technologies, applications, methods for collecting, analyzing and visualizing any information with business value. It provides a clear understanding of a company’s current and historical data and prioritizes descriptive analyses.
BI also includes a set of data analysis and visualization tools that display insights on interactive dashboards and perform ad hoc requests.
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Much emphasis is placed on automating the process, making it easier for non-technical business users to interpret the information provided to them.
In short, business intelligence aims to provide companies with valuable data insights to facilitate their current decision-making processes and improve their operations on a daily basis.
Thanks to better data processing and the continuous monitoring of the administration and efficiency of your activities – as well as the external environment – you can identify trends and patterns and quickly spot any inefficiencies.
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BI solutions offer high levels of customization, access to accurate data, and the ability to compare data from different sources – all of which allow you to see the big picture. This way you can make better decisions in no time.
ETL procedures and automated business processes allow you to work with greater efficiency, which helps you save a lot of time and reduce costs. In addition, ETL ensures data integrity, availability and security.
Business intelligence solutions allow you to build complex reports and high-quality dashboards that clearly show the insights and knowledge you gain from your data. Everything can be customized to your specific needs and requirements.
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Cloud-based BI tools give you access to your data instantly, anytime, anywhere. You can also give other team members access to relevant information so they can use the data as well.
Optimize the way your database and systems work and manage your data better, so you can get rid of the parts that are irrelevant and focus only on the information that brings real value to your business.
Fine-tuned company data and optimized data flow provide better operational agility. Your systems will be able to run faster and handle more processes.
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Data science focuses on aggregating, analyzing and optimizing data – collected and stored by data engineers – and then presenting it to the business.
It involves hypothesis testing, providing predictive models that support forecasts, and making plans for the long-term future.
Naturally, both BI and DS fall under the umbrella of data management and visualization, while providing actionable insights. However, data scientists would rather take an exploratory approach to both structured and unstructured data, saving descriptive analysis for the BI experts.
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In short, data science is excellent at recognizing current and future opportunities and serves business owners and decision makers as a basis for strategic planning.
Data science provides real-time information so you can quickly make decisions and implement necessary changes in your future plans.
DS provides comprehensive analytical models that not only facilitate decision-making and strategic planning, but also help you discover and understand trends and find unseen patterns.
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A well-designed IoT platform will collect and organize data from multiple devices and engage artificial intelligence algorithms to increase both customer and business value of your current operations and future strategies.
Machine learning models enable continuous monitoring of the effectiveness of your activities and also support predictive maintenance and detection of anomalies in your products and processes.
The nature of data science is about moving forward so that you can make proactive decisions and steer your business in the right direction, be one or more steps ahead of your competitors while meeting the future needs of your customers.
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There is a rather blurred line between business intelligence and data science, and the responsibilities of BI and DS teams can sometimes overlap. It can also vary from one IT company to another. But we know one thing for sure – combined BI and DS become a powerful weapon against information chaos, insufficient knowledge, ignorance and weak predictions. BI and DS offer complementary perspectives while serving one purpose, which is to support both long-term and short-term decision-making processes.
At Future Processing, we offer business intelligence as well as data science services. We realize that it is sometimes difficult to determine who is needed without knowing the root of the problem. Whether you’re looking for specific people or you have a problem and you’re wondering if it’s possible to solve it and how much it costs – you can contact us and we’ll see how we can help you.
Data science and engineering Process data, base business decisions on knowledge and improve your daily operations. Let’s work together Business Intelligence (BI) encompasses the technological tools and strategies companies use to gain data-driven, actionable insights. These insights inform strategic decision-making across organizations.
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Today, companies that don’t use BI strategies in some way, shape or form are likely lagging behind their competitors. 85% of companies report that they are trying to be data-driven, but only 37% report that they have been successful
Modern business intelligence (BI) is a concept of the digital age, but the concept itself has been around for decades. The definition of BI, first coined by IBM researcher Hans Puter Luhn, who wrote A Business Intelligence System in 1958, has evolved along with the business world and technological tools that use it.
Today, it refers to using data to create insights that create value for businesses in a number of ways, including, but not limited to, optimizing marketing, sales, operations, and performance tracking.
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The primary difference between business intelligence concepts of the past and BI as it is known today is the organizational approach it takes.
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In the past, companies took a top-down approach to business intelligence, which was driven by IT teams that delivered information and managed requests and questions through a queue. This led to long reporting cycles and delays in data that limited the ways it could ultimately be used to make decisions and drive strategy.
Modern BI is being democratized across organizations with the goal of creating and maintaining a data-driven culture. When done successfully, employees at all levels are data-informed and able to use it to gain insights, be strategic, and make smart business decisions on behalf of the company. Technological tools now make data more accessible via both platforms
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