Business Intelligence Developer Income U.s.a. – The average business intelligence developer salary is $92,540 to create our salary estimates, starting with data published in public sources such as the US Bureau of Labor Statistics (BLS), Foreign Labor Certification Data Center (FLC) Show More
The average salary of a business developer in the United States is $92,540. Generally, the salary of a business developer is between $70,000 and $121,000 per year. The average hourly rate for business developers is $44.49 per hour. The salary of a business developer is affected by location, education, and experience. Business developers earn the highest average salaries in Washington, California, Oregon, New York, and Nevada.
Business Intelligence Developer Income U.s.a.
Average business intelligence developer salaries in Washington, California, and Oregon are the highest in the U.S. States with the lowest average business intelligence developer salaries are Arkansas, North Dakota, and Wyoming.
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Business developer salaries at Meta and Apple are the highest paid according to our latest salary estimates. Additionally, the average accountant salary at companies like Google and Ropes & Gray is highly competitive.
The average business intelligence developer salary varies by industry: The average business intelligence developer salary in the healthcare industry is $92,515, the highest of any industry. The average salary for a business developer in the financial industry is $92,137. Real estate developers earn an average salary of $88,531, the lowest of any industry.
Washington pays the most intelligent business developers in the United States, with an average salary of $110,901 per year or $53.32 per hour.
You know you’re being paid fairly as a Business Intelligence developer if your pay is close to the median wage for the state you live in. For example, if you live in California, you should be paid close to $ 109, 094 per year. BI processes and tools analyze business data, turn it into actionable insights, and help organizations make better informed decisions.
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Most companies collect large amounts of business data every day – flowing in from enterprise resource planning (ERP) software, e-commerce platforms, supply chains, and many other internal and external sources. To really take advantage of this data, and use it to make data-driven decisions, they need a modern business intelligence (BI) system.
Business Intelligence refers to the processes and tools used to analyze business data, turn it into actionable insights, and help everyone in the organization make better informed decisions. Also called a decision support system (DSS), a BI system analyzes current and historical data and presents the findings in easy-to-digest reports, dashboards, graphs, charts, and maps that can be shared across the company.
BI is sometimes called “descriptive analytics” because it explains how businesses operate today and how they operated in the past. It answers questions like: “What happened?” and “What needs to change?” – but it does not understand why something happened or what might happen next.
Business Intelligence and Business Analytics are two terms that are often used interchangeably. Is there a difference? Currently there is no consensus. That said, the general difference is that business focuses on what happened in the past and what is happening now (explanatory analysis). While business analysis focuses on:
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But at the end of the day, both BI and business analytics are important – working together to provide companies with the four types of analytics (descriptive, diagnostic, predictive, and prescriptive) and big-picture insights that decision makers need.
What is the difference between business analytics and business intelligence? The correct answer is: everyone has an opinion, but no one knows, and you shouldn’t care.
Regardless of the label used, the important thing is that organizations have the tools and technology they need to get answers to their business questions, solve the problem at hand, or achieve specific goals. This is why a number of major software vendors have begun to integrate BI and business analytics in a single cloud platform, providing organizations with all the analytical capabilities they need in one place – and displaying the entire taxonomy debate.
A successful BI program sheds light on how to increase profits and performance, discover problems, optimize operations, and more. Here are just a few of the benefits of BI:
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There are many different tools used in business systems. Here are some of the most common:
BI reporting – presenting data and insights to end users in a way that is easy to understand and implement – is fundamental to every business. Reports use summaries and visual elements such as charts and graphs to show user trends over time, relationships between variables, and more. They are also interactive, so users can cut and dice the table or drill down into the data as needed. Reports can be automated and sent out at regular, pre-defined times. Pages – or specific applications and immediate production.
Query tools allow users to ask business questions and receive answers through an intuitive interface. With modern query tools, sending questions can be as simple as asking Google (or even Siri) a question – such as “Where are shipping delays occurring?”, “Did quarterly sales meet their goals?”, or “How many widgets were sold? Yesterday?”
Dashboards are one of the most popular BI tools. They use charts, graphs, tables, and other types of continuously updated data visualizations to monitor pre-defined KPIs and other business metrics – and provide an overview of near-term performance. Managers and employees can use interactive features to customize the information they want to see, drill down into the data for further analysis, and share the results with other stakeholders.
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The ability to visualize data and see it in context is one area where BI really shines. Charts, graphs, maps, and other visual formats bring information to life in a way that can be quickly and easily understood. Trends and outliers are very apparent. Colors and styles paint the story behind the data in a way that columns and rows in a spreadsheet never can. Data visualization is used throughout BI systems – in reports, as answers to questions, and in dashboards.
Online Analytical Processing (OLAP) is a technology that powers data discovery in many business intelligence systems. OLAP allows for rapid, multidimensional analysis across large amounts of data stored in data warehouses or other centralized data storage.
Data preparation involves gathering multiple data sources and generally preparing them for data analysis. Using a process called extract, transform, and load (ETL), raw data is cleaned, classified, and then loaded into a data warehouse. A good BI system automates many of these processes and allows for defining dimensions and measures.
A data warehouse collects data from multiple sources that has been cleaned and formatted so that it can be accessed by BI and other analytics tools.
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Today’s BI tools make it easier for everyone across the organization to access, analyze, and act on current and historical data. Here are some examples of BI use cases in various business areas:
Business intelligence has been around for over 30 years and traditionally, it has been driven by IT. Questions are sent to the IT team and answers are provided to the business in the form of static reports. If there are follow-up questions, they are sent to IT again and are usually placed at the back of the queue. This time-consuming process has been replaced by modern BI – which is more interactive.
Modern, self-service BI tools allow business users to query data themselves, configure dashboards, generate reports, and share their findings from a browser or mobile device – all with minimal IT involvement. Recently, artificial intelligence (AI) and machine learning technologies have made this process easier – and faster – by automating many BI processes, including data discovery and reporting and visualization.
Increasingly, companies are choosing cloud-based BI tools that connect to more data sources and are available 24×7 from anywhere. And they are choosing solutions that offer BI – BI that is embedded directly into workflows and processes so that users can make better decisions now and in context.
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Today’s most modern BI platforms combine business intelligence, advanced analytics and forecasting, and planning tools in a single analytics cloud solution. They are enhanced by AI and machine learning technologies, they can be embedded in any process, and they democratize BI and analytics by making it easy to use for everyone – not just IT departments or professional analysts.
Business intelligence is focused on analyzing past and present data to draw a picture of the current state of the business. Data science uses the same cross-disciplinary approach to data analysis, using Statistical methods and models to reveal hidden information and predictions from the text Structured and unstructured data.
Business intelligence is descriptive, giving an understanding of what is happening now and what happened in the past. Business analytics is a synonym for data analysis techniques that can predict what is going to happen and show what is needed to create better results.
Business intelligence tools work together to turn data into actionable insights. Many of these operate “under the hood” to prepare, mine, store, and process information so that it can be accessed by the BI system. Others are focused on helping business users interact with information and
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