Business Intelligence Nedir – The concept of business intelligence was first used in Luhn’s article published in IBM Magazine in 1958. However, the accepted view in the literature is that the first definition of business intelligence was made by Howard Dresner in 1989. There are several definitions of business intelligence in both academic and practical literature.
In short, Business Intelligence or BI (Business Intelligence) is all processes and methods that help to make business decisions and set strategies by processing large amounts of data and making the raw data useful and meaningful.
Business Intelligence Nedir
Business intelligence has become more important than ever because the data created by individuals on the Internet and stored by companies has grown to enormous proportions as technology has evolved. It has become an indispensable collection of practices used to identify risk factors, design marketing and sales activities, and improve production and management processes.
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Raw data is taken from the company’s database, this data can be in different formats and structures. The data is cleaned, organized and converted into a data warehouse. Using the business intelligence system, users can run queries, create reports or perform any other analysis they need.
Business intelligence applications usually use data collected from a data warehouse or a data warehouse directory. A data warehouse is a copy of transaction data, which facilitates decision support. However, not all data warehouses are used for business intelligence. Not all business intelligence applications require a data warehouse. This website uses cookies to provide the necessary functions and improve the user experience. By using this website, you agree to the use of cookies as described in the CyberArts Privacy Policy and Cookie Policy. Accept Reject
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What Is A Data Mesh — And How Not To Mesh It Up
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All cookies that may not be particularly necessary for the functioning of the website and are specifically used to collect personal data from users through analytics, advertisements, other embedded content are called non-necessary cookies. It is mandatory to obtain user consent before implementing these cookies on your website. If we talk about the definition first, business intelligence includes all the processes that make raw data meaningful and useful. This allows the data to be used in decision-making mechanisms as information with added value for decision-makers. In other words, it supports the actions of companies in the future. Workspaces are typically areas where data is processed end-to-end. Business Intelligence can be found in many industries. The most important ones are finance, telecom, energy, public, health, FMCG, etc.
Now that we have the definition in mind, let’s talk about the components. It includes logical solutions such as reporting, multidimensional analysis processes, data mining, process mining, modeling, benchmarking, forecasting.
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Data warehouse: First of all, a database in which data from various sources can be queried easily, quickly and precisely.
It is necessary to manage data from one central to be able to communicate between data, see the relationship between them and create a story from the data.
Data Warehouse (Data Mart): Subsets of data warehouses. A data warehouse consolidates databases, while data marts are usually smaller and focus on data for a specific topic or need. They facilitate analysis through the corresponding data marts without dealing with all the complexity in data warehouses.
Mobile Business Intelligence
OLAP (On-Line Analytical Processing): This is a type of approach that allows multidimensional analysis of data. Unlike relational databases, they are structures that create data through repetition, use it for reporting and analysis, and allow quick access to data. The reason for the fast operation of OLAP systems is that the data is pre-calculated. It provides interpretation and reporting of existing data.
OLTP (On-Line Transaction Processing): It is a database system that is usually based on relational databases and is constantly processed (insert, update, delete…). These normalized databases respond to fast query operations. They do not contain data duplication due to relationships between tables.
ETL (Extract, Transform, Load): It is the process of extracting, cleaning, combining, transforming the data to be used from the sources (database / data warehouse) and loading the data according to the business processes. As large amounts of data are extracted from operational systems and uploaded to data warehouses or data marts, they go through the ETL process. The aim is to ensure that the data is used as effectively as possible.
Business Intelligence & Analytics Solutions
Dashboard: It is the translation of data collections into visual elements. Versatile reports with graphs and pivot support versus flat reports. The report type of the dashboard makes it easy to see data as it uses many visualization techniques.
If we look at the developments over the last few years, we find that “data” is one of the most important concepts of business and information technologies. The value and investment in data is increasing.
For companies to survive in today’s competitive environment, they must manage the data they collect by developing the right strategies. This is where the term Business Intelligence appears.
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The most important feature of business intelligence solutions is that they offer companies efficiency in reporting and analysis. It helps to make the right decisions by increasing visibility and competence in the most risky situations such as sudden and urgent decisions.
It is possible to see the tools in this list, which was created by Gartner based on user feedback and ratings. The concept of business intelligence has been around for over a century and a half. At its core, business intelligence is about understanding the data and relationships between data in a way that guides decision making and action. From a technology perspective, BI is a suite of tools for transforming raw and scattered data into meaningful business insights. What needs then paved the way for the development of this concept?
Companies put a lot of effort into developing reports from unorganized piles of data and deriving values from those values, an effort that was very time-consuming. The need to accurately visualize the data, display it in one place and derive insights from that data paved the way for the development of the concept of business intelligence.
Sap Discovery Center
Power BI is a business analytics service for visualizing and analyzing all your data in one place. In other words, Power BI is a business analytics suite that analyzes and interprets data. In short, it visualizes your business. It generates quick responses through rich dashboards that can be viewed on any device. Microsoft Power BI is a SaaS platform that enables anyone to easily access their own data, create live dashboards and reports and explore data at any time through interactive visualizations. With MS Power BI, you can view all your data in one place, regardless of where the data resides, enabling a consolidated view of business operations. Power BI consists of three complementary applications.
Use Power BI Desktop, a tool for visual data exploration and reporting. Get Power BI Desktop for free and Power BI Pro for a low monthly fee per seat.
Create a data-driven company culture. Share interactive reports faster by using Power BI Pro for self-service analysis and collaborate on those reports with your team.
What Is Self Service Business Intelligence (self Service Bi)?
Use Power BI Mobile, a suite of native, interactive mobile apps for Windows, iOS and Android devices that provide secure access to Power BI dashboards and reports from any device.
Use one of the largest and fastest growing business intelligence platforms in the world. Create and share compliant interactive data visualizations.
5. Integrates with other Microsoft products and cloud services including Azure Data Warehouse, Azure Streaming Analytics, Azure ML, Office 365
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The Power BI dashboard is a set of data visualizations or charts based on one or more reports that make it easy to present insights – no specialization required. One advantage of Power BI is that the dashboard is live. For example, when a visualization in the dashboard is connected to a real-time data source, the visualization automatically updates itself, providing faster insights and generating reports immediately.
A dashboard can contain visualizations of multiple reports. Customizable dashboards – You can pin or add any chart from any report to any dashboard. You can also add an image (such as a company logo) from an Excel file to the dashboard. It is even easier to create a dashboard when importing data from popular SaaS platforms such as Google Analytics, Marketo, Salesforce, ZenDesk. Once connected to a SaaS platform, Power BI displays the data in preconfigured dashboards and reports optimized for that solution, so you can start exploring the value of your data in minutes.
In Power BI, dashboards are not only visual, they are interactive tools. If you want to delve deeper into the data presented on a dashboard, you can examine the underlying reports to see the details.
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With an easy-to-use interface, Power BI enables anyone to create rich, interactive reports. In Power BI, the said report is a series of charts, also known as visualizations, based on the same underlying dataset*. You can create a report from scratch, select an existing report, or apply a preset report template created for a specific dataset. Now, how can we customize the reports? Reports can be customized by changing the visualizations in an existing report or adding new visualizations. If the same data has different headers to check, it is possible to create reports of many variations of one data set.
If a report contains the visualizations you want, you can pin the report or a subset of its contents to the
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