By: Andy Kim
Business Intelligence Consultant
The business intelligence (BI) industry has really taken off in the last few decades, where more and more businesses are realizing the tremendous value in having a great business intelligence solution. With this exponential growth, BI strategy and implementation is constantly evolving. Three major trends that the industry is currently experiencing are:
1) An increasing shift towards self-service BI.
2) An increasing integration of BI with big data technologies.
3) An increasing use of cloud technologies in BI.
Why are many companies shifting towards self-service BI solutions?
Gartner describes self-service BI as “… end users designing and deploying their own reports and analyses within an approved and supported architecture and tools portfolio.” Some popular self-service BI tools include Microsoft Power BI, Tableau, and Qlikview. As you can see in the diagram below, there are many other options available. Some companies are discovering that choosing more than one tool best suits their particular environment and business objectives.
One reason for the shift towards self-service BI is lower costs. Many companies do not have or cannot afford the technical resources to implement some of the traditional (and more complicated) reporting tools. They are seeking tools that allow less technical business users to create their own reports. This will in turn relieve some of the workload in the IT department. In addition, the price for using self-service BI software, such as licensing costs, is significantly lower in many cases. This affordability is opening a market that small and medium businesses can now take advantage of.
A second reason for the shift towards self-service BI is the time savings. As a business, we understand that time is money. With minimal training, business users can create reports in a matter of minutes. They can extract data from various sources very easily, then model the data and create visually rich reports. Under the more traditional methods, there are typically many meetings between IT and business users to create reports. Under the self-service BI model, the business user and the report developer are one in the same. This eliminates the need for cumbersome, excessive back and forth communication, which can save chunks of time and avoid miscommunication.
A third reason for the shift towards self-service BI is the great flexibility and agility it provides. Multiple business users can create reports for their respective departments at their own pace. They can pull data from various sources easily, and they can use myriad new visualizations that are constantly being added. Self-service BI tools are very flexible in many different ways.
What is the need for integrating with big data technologies?
According to Wikipedia, “big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them.” With the emergence of modern day big data sources such as the Internet of Things (IoT), clickstream data from web traffic, and log data, we need new technologies to store and process this enormous volume of data. Due to the sheer amount of data, we need the distributed and fault-tolerant nature of these technologies to speed up the process to store and prepare this data for analysis. Big data technologies allow us to work with unstructured, semi-structured, and structured data so that we can prepare and aggregate this data to a more manageable level. In this manner, we can integrate it with the more traditional BI tools. This trend continues to emerge, but thanks to integration with big data technologies, companies are now able to gather more complete intelligence on areas that were not possible before.
How is the cloud being utilized in the context of business intelligence?
As the paradigm shifts to cloud computing more and more, the BI industry is increasingly adopting this trend as well. In previous years, cloud computing was somewhat limited. For example, there were limitations on size of data and functionality. As cloud technologies mature, the functionality becomes ever-increasing, while limitations are mitigated. As BI professionals we can leverage the generic benefits of the cloud, such as:
1) The cost-saving nature of the cloud – There is no need to purchase hardware, and there is no need to have personnel to maintain that hardware.
2) The time-saving nature of the cloud – There is no need to appropriate large budgets for hardware/software setup. Computing power can be available in a matter of minutes rather than weeks or even months or years.
3) The ease of scalability – It is easy to add more processing power with just a few clicks and keystrokes, and this processing power can be scaled as needed on an increasingly granular level.
4) The accessibility factor – Because the data is on the cloud, it is easier to access from anywhere (including mobile devices).
More specifically, companies are creating BI applications that are native to the cloud. A few examples of cloud reporting software include Power BI Cloud Platform, Tableau Online, and Excel in Office 365.
In addition, companies are creating entire BI ecosystems in the cloud. A few examples of cloud data warehousing products include Microsoft Azure SQL Data Warehouse and Amazon Redshift. These databases are optimized for business intelligence functionality. More recently, we are seeing big data technologies being incorporated into the cloud with such products like Azure HDInsight, Amazon EMR, and Amazon Machine Learning. The incorporation of these technologies is, in effect, guiding us towards the transition to ACID Intelligence that we previously discussed a few weeks ago.
It will be exciting to see how the industry continues to evolve, and where we will be taken next.