5 Business Intelligence Technologies in a Nutshell

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For even small businesses, the magnitude of available data each day is rapidly increasing. If our problem a couple of decades ago was the inability to make good management and technical decisions due to insufficient information, nowadays we can say it’s because there’s too much information.

More people than ever are recognizing the importance of business intelligence, which can be defined as the ability to glean value from big data— from the tools and techniques to discover, gather, and analyze digital data.

For decision makers who want to improve business intelligence, what business intelligence technologies do you need to consider in producing actionable Business Intelligence?

1. Data Warehousing

A data warehouse (DW, DWH), or an enterprise data warehouse (EDW), is a system that can be used for data analysis or with a reporting software. Say you work for a company that uses multiple sources to keep track of transactional data. You want to view order data from the past 5 years. Just thinking about exporting these lists and sifting through them all gives me a headache. You can use a data warehouse to integrate data from one or more disparate sources, which creates a central repository of data. Basically, this maintains a copy of information from the source transaction systems so that you only need a single query engine to view the data you need. A data warehouse is useful if you want a big picture of your organization/enterprise, to keep historical data, to improve the quality of your data (more consistent, less bad data, etc.), or to combine all data from different sources into a single data model.

Data Warehouse

2. Dashboards

A dashboard is an informative, easily readable, usually one page, real-time user interface that shows a visual representation of data using graphs and charts. By real-time, we mean that most dashboards can be pulled up on a web page that is linked to a database so that the data shown is constantly updated and refreshed. Dashboards show summaries, key trends, comparisons, and exceptions in both current and historical data. This can enable you to see at a glance the performance and status of different parts of an organization and to make informed business decisions. For example, a sales dashboard may show the different product lines sold, the performance of sales people, or the sales numbers for different regions of the world. Many dashboards have a drill capability and will allow you to instantly discover more detailed information or view the data from another angle. The key benefits of dashboards are the ability to visualize data anytime, to easily spot trends, to keep track of key performance indicators, and to quickly gain total visibility or snapshots without having to run multiple reports.

Ad Hoc Reporting

3. Ad Hoc Reporting

Ad hoc as a Latin phrase simply translates to “for this”. It refers to a solution that was created for a specific question or problem and is not meant to be changed or adapted for different tasks. Ad hoc reporting is a common business term that references a report or model that is produced for the purpose of answering a specific business question. The main reason for ad hoc reporting may be to fill in a blank on an as-needed basis where a regular report did not.  Or, it may be used to aid the making of an important business decision. For example, as the manager of a shop, you may need to decide whether you should purchase new equipment. You can create some ad hoc reporting to determine if purchasing the equipment would increase profitability. Lastly, the data retrieved for an ad hoc report will be specific to answering one question, but can also be analyzed even deeper using a Web Report or a dashboard designer.

4. Data Discovery

Sometimes called knowledge discovery, data discovery is essentially a pattern finding tool. Finding an understandable structure among dozens of fields in large relational databases is usually difficult. Data discovery software can analyze a large amount of data to locate information from that set and extract previously unfound patterns, outliers, associations, and correlations. Because the uses of data discovery are so broad and are frequently also applied to forms of large-scale data, information processing, and applications of computer decision support systems, many times the term is used as a buzzword or to add value for marketing purposes. One example of data discovery in play is if you use the data discovery capacity of a software to analyze regional sales patterns of coffee sales. You may discover that college students buy more iced coffee Monday to Friday, and iced coffee buyers are more likely to purchase a doughnut. You could use this newfound information to increase revenue buy moving promotions on iced coffee to weekends, and offering a deal for doughnuts with iced coffee.

Data Discovery

5. Cloud Data Services

More likely than not, you’re already using some sort of cloud based service, whether it’s for business or personal purposes. An increasing number of businesses are flocking to the cloud data service providers due to the new efficiency and capabilities they can offer. Using cloud data services means you can access IT resources, data storage, customer relationship management, enterprise resource planning, and marketing automation from anywhere. Data integration, transformation, management and security activities are no longer tethered to physical bodies. This means you can access information from anywhere at any time, providing unprecedented speed, agility, reliability and security. You can choose to use private, public, or hybrid clouds given the type of data integration and data quality maintenance you need. With low overhead and easy scalability, it’s no wonder many businesses are jumping on the cloud bandwagon.

Cloud Data Services

Which BI technologies have you tried?

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