VIDEO: Business Intelligence Tutorial for Beginners

This is a technology advice guide to business intelligence. It will show you how to find business intelligence software for your business. Business intelligence, Lucy, refers to applications that transform data into meaningful information that help businesses make better decisions. Business intelligence started in the late 1950s and helps businesses gain a competitive edge by supporting and improving their decisions with relevant, insightful information.

The rise in popularity of business intelligence is closely linked to the rise of big data. As technology has progressed and more activities have shifted to the internet, it has become possible to track and compile behavioral data like never before. To make informed choices, businesses need to base their decisions on evidence. Customers and businesses are always producing evidence of purchasing patterns and marketing trends. Companies like Walmart are utilizing data from the millions of customer transactions per hour.

The businesses that harness that intelligence first will gain a competitive advantage by predicting customer behavior. To best manage big data, a popular first step is taking an inventory of all the data your business produces using the extract, transform, and load method. Data warehouses aggregate data from across an organization and make it easier for other applications to quickly access them. Data and analytics and reporting exists in different formats, making it exceptionally difficult to draw conclusions and identify patterns without restructuring the data into a common format and housing it in a common area.

Data is stored in a data warehouse in dimensions and facts. Essentially simpler, narrower versions of data warehouses, data marts focus on a specific subset of data instead of storing data from across the entire company. Extract, transform, load. named for the process by which data is transferred into a data warehouse. ETL applications are for normalizing data in a central location. The degree of success by which data extracted from their source systems, ERP or CRM systems for example, influences the success of the rest of the process.

To prepare the data for storage in the data warehouse, the second stage of ETL applies rules to incoming data in order to clean or normalize it. Now that the data have been extracted from their source systems and normalized through the transform phase, it's ready to be loaded into the central database, most commonly the data warehouse. A very popular data storage framework, Hadoop is an infrastructure for storing and processing large sets of data.

Analyzing big data. Regardless of whether businesses choose to store their data in a data warehouse or run queries on the source system, the analysis part of business intelligence is what produces the insight that makes the entire field so appealing. also known as data discovery. Data mining involves automated and semi-automated analyses of sometimes large sets of data to uncover patterns and inconsistencies. Of the standard processes performed by data mining, association rule learning presents the greatest benefit.

It's the type of analysis that now connects incredibly complex chains of events and helps users find correlations that would have stayed hidden otherwise. Perhaps one of the most exciting aspects of business intelligence, predictive analytics applications function as an advanced subset of data mining. Three forms of predictive analysis are predictive, descriptive, and decision. Predictive models search for correlations between a particular unit of measurement and at least one or more features pertaining to that unit.

The goal is to find the same correlation across different sets of data. Descriptive analytics works well for helping to summarize information such as unique page views or social media mentions. Decision analytics takes into account all the factors related to a particular decision. The processing arm of the Hadoop framework map produce processes data in its large storage location rather than transporting the data across the server to the location of the processing software.

Synonymous with text mining. Text analytic software comes text analytic software comes unstructured data to find patterns hidden within larger sets of text data. Data comes in three main forms. structured, semi-structured, and unstructured. Utilizing this data is often crucial to figuring out how to move forward. Business intelligence reporting focuses on the presentation of the mechanics of BI and how business data is stored. Online analytical processing enables users to query data warehouses and create reports that view data from multiple perspectives.

One of the most popular trends in business intelligence, data visualization allows companies to graphically display the results of data mining or other analytics. Another albeit narrower form of data visualization, dashboard functionality or refers to the interface that represents specific analyses. Far from a misunderstood buzzword, business intelligence is being implemented in a number of different organizations to great effect. TWWI's latest survey showed the big data and business intelligence are both standardized in many businesses and are seen as an opportunity.

Another survey showed that businesses accessing timely, reliable data is their biggest information management obstacle. And just over a quarter of businesses said business intelligence helps them gain a competitive advantage. While the number of organizations who have adopted business intelligence and gained a competitive advantage remains in the minority. One of the most difficult areas of implementing business intelligence lies in finding the proper expertise trends.

In-memory processing utilizes RAM instead of disk or hard drive processing in order to read information. Accessing information in this manner increases the application performance exponentially. As usability and visualization are becoming more important, the design of reporting mechanisms and ease of use of analytics functions are being driven towards a lower barrier of access. The key to business intelligence involves centralizing the information in a data warehouse before it's analyzed.

So, the data is cleaned and formatted properly. From a business perspective, O2 Ireland wanted to get the most out of its relationship with its customers, but it need to know which ones to target. O2 Ireland had the same data problem that plagued many businesses today. A number of systems were capturing data, but the data wasn't unified. The first step was to create a central data environment. OT was able to segment the 65% of their customers who stayed in the country after they purchased SIM cards and to target them.

They launched location specific marketing that's been successful in driving foot traffic to brick and mortar locations. Instead of focusing solely on the technology, they focus on what the technology could do for their business. Now that you've learned the basics, head over to our website where you can download the complete guide or read more about how business intelligence software can help your business.

This transcript was generated automatically from the video's captions and may contain errors.