Precisely Simply Ways To Acquire Business Intelligence Tasks In Visual Workshop 2017 – Business intelligence (BI) is a technology-based process that analyzes data and helps executives, managers, and employees make business decisions. As part of the BI process, organizations collect data from internal IT systems and external sources, prepare it for analysis, query the data, and create data visualizations, BI dashboards, and reports to provide analytical results to business users for operational decision-making and strategic planning.
The primary goal of BI initiatives is to make better business decisions that enable organizations to increase revenue, improve operational efficiency, and gain a competitive advantage over their business rivals. To achieve this goal, BI includes analytics, data management and reporting tools, as well as various methodologies for data management and analysis.
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Business intelligence architecture includes only BI software. Business intelligence data is typically stored in a data warehouse built for the entire organization or in smaller warehouses that hold subsections of business information for individual departments and business units, often linked to enterprise warehouses. In addition, data lakes based on Hadoop clusters or other big data systems are used as repositories or landing pads for BI and analytics data, especially for log files, sensor data, text, and other types of unstructured or semi-structured data.
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BI data can include historical data and real-time data collected from source systems, enabling BI tools to support strategic and tactical decision-making processes. Before it can be used in BI applications, raw data from different source systems typically must be integrated, consolidated, and refined so that BI teams and business users can analyze accurate and consistent data.
Initially, BI tools were primarily used by BI and IT professionals to manage queries and create dashboards and reports for business users. However, business analysts, executives and employees are using business intelligence platforms themselves, with the help of self-service BI and data discovery tools. A self-service intelligence environment enables business users to query BI data, create data visualizations, and create dashboards themselves.
BI software often includes forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis, and big data analytics. A common example is predictive modeling, which allows analysis of various business scenarios. In most cases, however, advanced analytics projects are led by individual scientists, statisticians, predictive modelers, and other skilled analytics professionals, while BI teams directly query and analyze business data.
In general, the role of business intelligence is to improve an organization’s business operations using relevant data. Companies that effectively use BI tools and techniques can translate their collected data into valuable insights into business processes and strategies. Such insights can be used to make better business decisions that increase productivity and revenue, leading to faster business growth and higher profits.
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Without BI, organizations cannot benefit from decision making. Instead, executives and employees primarily base important business decisions on other factors, such as accumulated knowledge, prior experience, intuition, and gut feeling. Although these methods can produce good decisions, they are also fraught with the potential for error and error because of the lack of data on which to base them.
A successful BI program brings a variety of business benefits to an organization. For example, BI allows C-suite executives and department managers to monitor performance so they can act quickly when problems or opportunities arise. Analyzing customer data makes marketing, sales and customer service more effective. Supply chain, manufacturing and distribution problems can be identified before they cause financial damage. HR managers can better track employee productivity, labor costs and other workforce data.
BI initiatives also provide narrow business benefits—among them, making it easier for project managers to track the status of business projects and providing organizations with competitive intelligence on their competitors. In addition, BI, data management and IT teams themselves benefit from business intelligence, using it to analyze various aspects of technology and analytics operations.
Business intelligence integrates a broad set of data analysis applications designed to meet a variety of data needs. Most are supported by self-service BI software and traditional BI platforms. A list of BI technologies available for organizations include:
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Advertising Analysis. Also known as a custom query, it is one of the core elements of modern BI applications and a key feature of self-service BI tools. It is the process of writing and developing questions to analyze specific business problems. Although custom queries are usually created on the fly, they are often run regularly, with the results of analytics included in dashboards and reports.
Online Analytical Processing (OLAP). One of the first BI technologies, OLAP tools allow users to analyze data across multiple dimensions, especially for complex queries and calculations. In the past, data had to be extracted from the warehouse and stored in large volumes of OLAP cubes, but OLAP analyzes can now be performed directly against a columnar database.
Mobile BI. Mobile business intelligence uses BI apps and dashboards on smartphones and tablets. Often used more for data analysis, mobile BI tools are typically designed with an emphasis on ease of use. For example, a mobile dashboard can display two or three data visualizations and KPIs so they are easily visible on the device screen.
Real-time BI. Real-time BI applications analyze data as it is created, aggregated, and processed to provide users with an up-to-date view of business operations, customer behavior, financial markets, and other areas of interest. The real-time analytics process often includes real-time data and supports the use of decision analytics such as credit analytics, stock market analysis and targeted advertising recommendations.
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Operational Intelligence (OI). Also called operational BI, it is a type of real-time analytics that provides information to managers and frontline workers on business operations. OI applications are designed to support operational decision-making and act on issues faster – for example, helping center agents resolve issues for customers and logistics managers.
Software. SaaS BI tools use cloud computing systems to provide users with data analysis capabilities in the form of a service, typically priced on a subscription basis. Also known as cloud BI, the SaaS option increasingly provides multi-cloud support, allowing organizations to deploy BI applications on a variety of cloud platforms to meet user needs and avoid vendor lock-in.
Open Source BI (OSBI). Open source business intelligence software typically includes two versions: a free community edition and a subscription-based commercial edition with vendor technical support. BI teams also have access to the source code for development. In addition, some BI tool vendors offer free editions, primarily for individual users.
Embedded BI. Business intelligence tools put BI and data visualization functionality directly into business applications. It allows business users to analyze data within the applications they use to do their jobs. Embedded analytics features are typically included by software vendors, but enterprise software developers can also integrate them into homegrown applications.
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Default is BI. It is a process rather than a specific technology. It integrates BI applications and collaboration tools, allowing different users to work on data analysis and share information with each other. For example, users can interpret BI data and analytics results with comments, questions, and coverage using online chat and discussion tools.
Location Intelligence (LI). It is a specialized form of BI that allows users to analyze location and geospatial data, including map-based data visualization functionality. Location intelligence provides information about geographic elements in business data and operations. Potential applications include site selection, location marketing and logistics management for retail stores and corporate facilities.
Self-service BI and data visualization tools have become the standard for modern BI software. Tableau, Qlik and Spotfire, now part of Tibco Software, were early adopters of self-service technology and by 2010 were prominent competitors in the BI market. Most vendors of traditional BI query and reporting tools followed suit. Now, every major BI tool includes self-service features, such as visual data discovery and custom querying.
BI tools are available from dozens of vendors. Major IT vendors offering BI software include IBM, Microsoft, Oracle, SAP, SAS, and Salesforce, all of which purchased Tableau in 2019, as well as selling their own pre-purchase tools. Google is also in the BI market through its Looker unit, which it acquired in 2020. Other prominent BI vendors include Alteryx, Domo, GoodData, Infor Birst, Data Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot and Yellowfin.
What Is Augmented Analytics?
Although full-featured BI platforms are the most widely used business intelligence technology, the BI market includes other product categories. Some vendors offer tools specifically for BI use. examples include GoodData and Logi Analytics. Companies such as Looker, Sisense and ThoughtSpot target comprehensive and curated data analytics applications. Various
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