About 38% of conventional business are using business intelligence (BI) tools or have adopted a digital strategy. Close to 90% of all businesses are planning to digitize part of their operations and improve decision-making. The increased traction towards digital solutions makes IT managers or the entire IT enterprise the central focus in the organization. As an IT manager, you have to stay ahead of other managers when it comes to providing digital solutions to the business. That means you may require software and tools that will help you analyze data and use it to empower your department, and, teams in the organization. Power BI Reporting and Power BI Reports Scheduler (PBRS) are some data support tools that you can employ to improve decision-making. Here are some of the reasons that make data support and BI important in the IT enterprise.
What is the Role of an IT Manager?
Understanding the role of an IT manager helps you offer practical solutions to the organization. It also helps you know what each department expects from you and the IT enterprise. As the head of the IT department, you are responsible for ensuring all IT systems and infrastructure are working as desired. You also draw and execute the IT department’s budget.
Your role as the head of IT in the organization, means others are looking up to you as the organization implements its digital strategy. The sales and marketing team could need a tool or software that can predict market behavior. On the other hand, the production departments may require tools that provide more accurate focus for demand.
Other than supporting other teams, your department also requires data support tools. Today, you will hardly budget without a clear understanding of the department, organization, and industry trends. You must collect and analyze data from different areas when budgeting for your department.
To effectively serve your organization and remain competitive, you have to collect and analyze volumes of data. The data could be from the organization or collected through data mining tools. Regardless of the source, the data can only be meaningful when correctly analyzed. The burden on your shoulders demands data analytic tools or business intelligence software.
Difference Between Data Analysis and Business Intelligence Software
Few IT managers understand the difference between data analytic and business intelligence tools. In fact, some managers think the two terms can be used interchangeably. Although the two use historical data, they differ in application.
Data analysis is mostly about the future. You use data analytic tools to predict future trends in the organization and the industry at large. Business intelligence, on the other hand, uses past data to aid decision-making in your department or the organization at large.
Data and BI Complement Each Other
Although automation of decision-making is progressively gaining ground, software alone cannot solve the needs of your organization. Data remains the most important asset in decision-making. Use of wrong data always creates wrong outcomes, regardless of the sophistication of the analytic tool.
You should refine your data collection methods before thinking of purchasing BI software. Just like the popular maxim “garbage in, garbage out”, the quality of your decision depends on the input data. Data support tools should enhance data capture, as well as aid analysis and design making.
How Do You Protect the Integrity of Your Data?
Your role as the IT manager also includes maintaining the integrity of the data. Data integrity refers to preserving and guaranteeing data authenticity by protecting it from:
- Loss
- Modification or alteration
- Destruction or corruption
As you noted earlier, the decisions generated from BI intelligence software or data analytic tools are as good as the input data. But how do you protect the integrity of your data, or how do you ensure you are always using accurate data?
Backup the Data
Each day, you collect and store volumes of data. The stored data is used to help decision-making in the future. However, if the data is lost or corrupted, you may not make use of it when needed. To prevent such instances, always back up the data either in the cloud or store the backed up data on another premises.
Manage Access to the Data
Access to stored data should be limited through authorization. Only authorized staff should access data, particularly when the data is sensitive. Limiting access to data reduces the risk of modification or alteration.
Use Logs to Monitor the Data
Logs are used to detect changes or modifications made to the data. You can tell whether the modification was authorized or not by looking at the logs.
Audit the Data
Auditing ensures only accurate data is stored. Audit trails can help in verifying the accuracy of the data. Self-balancing ledgers can also be used to check the accuracy of the data.
Microsoft Power BI Reporting and PBRS
Data analytic tools like Microsoft Power BI reporting helps you maintain real-time data integrity and authenticity. The data analytic tool comes with special security features that help to protect alteration or modification of data. Power BI HELPS you to analyze large volumes of data at a time and make minute-by-minute decisions. Besides, the data analytic tool can be used by other departments.
The third party PBRS on the other hand, augments the Power BI Reports. PBRS simplifies your interaction with Power BI and dashboards, whether on premises or stored in the cloud. The software also comes with additional security features to enhance the integrity of data and reporting.
Bottom Line
Most businesses have already adopted or are planning to adopt digital solutions for solving various aspects of the business. One of the major applications of digital solutions is in simplifying the decision-making process. Organizations can now use business intelligence software and data analytic tools like Microsoft Power BI to aid decision-making.
As an IT manager, your job should include advising the management on the right data analytic tools to invest in, as well as protecting the integrity of the data being used.