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 from 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.
Here are some additional benefits of Ad Hoc Reporting:
- Self-service/Ad-hoc Reporting Makes Your Users Agile: Users are able to create, edit, and reuse reports and dashboards easily and more agilely than having to go to your development team every time they need a new report.
- Interactive and Self-Service Tools Can Be More Easily Accessed: Self-Service and Ad hoc tools are often web-based, meaning they can be accessed from any device connected to the web. This allows end users to be more mobile for data discovery and decision support anywhere.
- Additional Interactivity and Flexibility: Ad hoc doesn’t just mean the creation of reports, or even the editing of reports. Many self-service tools go beyond these functionalities with increased types of interactivity such as drill down, sorting, filtering, etc. These all allow end users to further explore their data for a more efficient workflow and for data discovery.
- Your Users Can Edit and Reuse Widgets for Easier Collaboration: Self-service analytics tools often come built in with the ability to save, edit, reuse, and share full reports, dashboards, or widgets. This can make collaborative decision making easier by giving multiple users the same data resources easily, while simultaneously enabling them to do their own data discovery.
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 by moving promotions on iced coffee to weekends, and offering a deal for doughnuts with iced coffee.
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.
Here are some additional benefits of using cloud for embedded reporting:
- Implement and Deploy Quickly: Deploying a solution in the cloud can be much faster than traditional deployments, with pre-built administrative structures, spinning up a cloud resource can be very easy. Many reporting solutions also may have a pre-installed executable available in cloud marketplaces such as AWS marketplace, for even faster deployment times.
- Create a Competitive Edge: Embedded reporting allows you to empower your users with enterprise level reporting capabilities faster and easier than developing them yourself. This can be a huge competitive advantage if your in a marketplace which has yet to meet this demand.
- Scale and Administer with Ease: Cloud can also enable you to scale up and down with ease. The rise of cloud is built on a foundation of efficient scaling, and as long as the embedded reporting system you’re using can match these capabilities you can easily scale for peak load times. JReport’s architecture was built to scale, allowing you to fully deploy in the cloud without affecting baseline performance. Its architecture includes failover capabilities so there are no single points of failure, as well as a variety of performance features such as load balancing to help make your reporting more efficient. The administrative capabilities JReport provides also help you limit the number of administrative resources needed to handle large numbers of customers by automating many of the workflows you would have to handle yourself if you developed out a reporting component.
Which business intelligence technologies have you tried?