Business Intelligence for IT Pros Resource Guide
The IT department is at the forefront of the implementation of a company’s new business intelligence software. Pressing concerns include security, and how the new technology might open up company data to potential vulnerabilities. Controlling the access of users to the new software is an important responsibility of the department. IT professionals helming the deployment of a new BI tool will need to be aware of data integration issues, and must work to consolidate structured and unstructured data sources within the new software.
Fundamentally, business intelligence relies on the gathering of massive amounts of data. Inevitably this data will contain sensitive information. It will also be accessed by a large audience. As some BI tools have a “centralized architecture” where all data is stored in a single place, it is easier for hackers to gain access to more information. It is also possible that employees leaving the company could take sensitive information with them. Fortunately, there are ways for the IT department to secure business intelligence and keep company data out of the wrong hands.
Perhaps the most effective and simplest form of BI security is access control. This ensures that individuals only have access to the data that they strictly need. By limiting the spread of sensitive information to where it needs to be, security risks are greatly mitigated. IT professionals implementing access controls have the option of placing the restrictions at the data warehouse level, where all the general data is stored, or at the reporting and presentation level, where the data has already been turned into charts, graphs, and visualizations.
Another major BI security challenge is the increased use of mobile devices. As more and more employees do all of their business from a phone or a tablet, more and more BI tools will respond by offering solutions with complete mobile access. Not only is data significantly less secure when it is outside of the company’s network, it is also more vulnerable to attacks when it is stored offline, on the actual mobile device. The IT department can foster both safe, increased mobile usage and business efficiency by ensuring that there are ways to secure their BI tool.
One key security measure is stricter authentication policies for mobile devices that access the BI information. Encrypting data, or coding it so that only authenticated devices are able to read it, is another major security measure. Data should also be “de-identified”, stripping it of all non-essential, personal information, to limit the consequences of a potential hacking.
Deployment is the process of fully implementing a new BI tool with the company’s existing infrastructure. A sound deployment plan is important to IT because it has a significant effect on the success of the tool and the ability of the department to empower employees to use it. A goal of the department at the onset of the deployment process should be communication with the end-users of the tool. IT should know what individuals want from a BI tool and what formats they are comfortable working with. If they don’t understand the technology or they are unfamiliar with the format in which information is being presented, it is unlikely that they are going to use it long-term. Ultimately, however, the word of the end-users should only be taken as a guide. It is up to IT to gain a nuanced understanding of their employees’ needs, their skillsets, and their limitations. Depending on the tool and the skill-level of the users, some training may be required. Not all vendors offer training as part of the cost of the tool, and this responsibility may fall to the IT department.
IT must also ensure that the new BI tool can be integrated with all necessary data, and that all data has been prepared for the integration. This can involve data cleansing, the process of removing bad or redundant information from a company’s database. It also involves consolidating together all of a company’s structured and unstructured data so that it can work with the new tool.
Most companies place pressure IT to see ROI from business intelligence very soon after the purchase. Implementation will likely not be successful, however, without a careful deployment plan that considers how business intelligence will merge with both employees and the company’s system.
One of IT’s major challenges is working with different types of data and data that comes from different sources. The right BI tool must be able to integrate many different kinds of data together into a single place. Companies work with multiple databases that may include different versions of the same data. They also work with both structured data that can be easily integrated into a database, and unstructured data, that is sloppy and needs to be organized before integration. It is important for IT to know what kind of data sources a new BI tool will accept, and to be sure that existing sources are compatible with the new tool.
The way that a company’s data is stored is vital to the success of a potential BI tool. Data storage becomes more important as the amount of data available to companies vastly increases. The more data, the greater the need of IT to have a place that can capture the information, manage it neatly, and have it ready for BI querying tools to plumb for insights. Many companies will have both structured and unstructured data coming from multiple sources, making the issue of a permanent storage location even more important.
Data warehouses gather together data in a new place and under a single format. This is necessary for BI tools to get the most accurate insights from data. This also provides an additional security measure for IT to prevent data loss by backing it up in another place.
Scalability addresses the ability of a business intelligence platform to scale its size and direction to fit the needs of a company. It is vital in ensuring that the right employees across a company are getting access to the right data. A scalable BI tool can be adjusted to accommodate additional users in certain given functions while still performing at a top level. A scalable tool should also be able to have additional capabilities added as needed. This allows the IT department to anticipate potential future needs.
Scalability is perhaps most important to IT departments at growing companies, or at companies that just see their responsibilities evolving and the number of users fluctuating.
- Why Scalability Matters to Your BI Project
- Tech Innovations that Improve Data Center Scalability
- Business Intelligence For a Smarter Future
- 10 Technical Features That Make a Business Intelligence Solution Scalable
- 3 Business Oriented Factors that Assist Business Intelligence Scalability
- Technology Components of a Scalable Architecture
Oftentimes, business intelligence tools take too long to produce reports or to return results from a query, and a crucial timeframe is lost. Speedy business intelligence tools can vastly improve a company’s efficiency. This is perhaps best embodied by Agile BI, a method of business intelligence which increases the speed at which final results are delivered. Quickly-produced insights based on real-time data lead to a speedier decision-making process, vital to a company’s business effectiveness.
Agile BI is important to IT departments not only for this speed, but also for its corresponding ability to empower employees with self-service access to reporting. This means that IT is involved less and less. As end-users gain more responsibility and oversight over reporting, not only are they given greater ownership of their insights, but there is less pressure placed on the resources of the IT department to provide support.
- Business Intelligence Picks up Speed
- Choosing a Business Intelligence Model that Improves Speed
- The Need for Speed with Big Data
Controlling user access to different parts of a company’s network is an important security technique that can help IT protect important information consolidated in a data warehouse. Access controls ensure that individuals are only viewing the data that they specifically need to do their job, and nothing more. Not only does this limit the spread of sensitive information to where it doesn’t need to be, but it also keeps data analysis simple by filtering out irrelevant information. By only providing employees with access to the right information, IT is ensuring that users won’t get caught up wading through data that they don’t need to be analyzing.