Infographic: 6 Business Intelligence Best Practices

Be Mindful to Keep these Practices throughout your Business Intelligence Project

Getting Business Intelligence Best Practices to work well is challenging.  Check out the 6 best practices outlined in this Infographic. Check it out and see how your organization stacks up. It’s easy to think that bigger is better, or assume you need to start from scratch. Actually its about having BI policies in place, keeping everyone on the team involved, having a clear scope, and making sure everyone is trained up well.

It is also important for a Business Intelligence project to have an analytics model that reflects the organization.

11 of the Best Practices for Business Intelligence

Business Team Brainstorming Data Target Financial Concept

Dennis McCafferty of CIO Insight recently wrote an article that addresses 11 of the top practices of Business Intelligence. With Business Intelligence controlling such key factors in today’s companies such as, analytics, business performance management, text mining and predictive analytics, it is crucially important to understand it. Let’s take a look into CIO Insight’s 11 best practices and see if you are already taking advantage of these.

  1.  Bigger Isn’t Always Better: Just because a solution can gather a large amount of data doesn’t mean that they are helping you get the most out of the data. McCafferty thinks that trustworthiness and immediacy are the key elements.
  2. Deliverable Value Over TCO: When your BI solution can deliver specific ROI, you will gain higher buy-in no matter the initial total cost of ownership.
  3. Take Stock of Current Resources: Taking advantage and leveraging the IT that your company already owns to support your BI solution is a top practice. You can then utilize that spending on something else that will make a larger impact.
  4. File-Formatting Resources: Since Business Intelligence uses more than 300 file formats, it is important that you are prepared and ready to use any one of them.
  5. Create BI Policies for Deployment: It is important to have BI policies in place such as how the data is collected, processed and stored. This will ensure higher level of relevance and accessibility.
  6. Go Team, Involve Business Leaders From the Outset: You need to remain on the same page as all of the different leaders and work as a big team to keep IT on the right path.
  7. The Only Constant? Change: Every thing is constantly changing and evolving so this will continue to test your BI deployment at all times.
  8. Limit Initial User Participation: It is better to start out slow and steady when introducing initial users. If not, it can lead to confusion, errors and confusion which will impact BI’s final impact.
  9. Define the Project’s Scope: A BI implementation should be taken in stages and a company must know how many users and functions will be needed over time.
  10. Training Day: In order for your BI project to be a success, you must take the right approach to training employees and make sure that they are properly educated and feel comfortable using the new solution.
  11. Support Self Service: The goal of BI is to pass along the project to the appropriate department. In order to do this you must support the training plans and keep this practice as a priority at all times.

 

Click here to read the original article.

Time for a Data Plan

Rear view of the business lady who is looking for the new business ideas. Blue growing arrow as a concept of successful business. Business icons are drawn on the concrete wall.

Data planning is quickly becoming a top priority in businesses across the globe. Ben Rossi dives into some key components that are making it vital for organizations to manage their data. According to Rossi’s post, there are two main components that factor into this. The first one is the increasing amount of data that is being pulled into organizations for analysis. As time progresses, so does the high volume of data and it is only speeding up as time ticks forward. Large quantities of data and information is a great thing but in order to retain any value from it, it must be managed the correct way.

Organizations are being faced with tougher compliance policies which is requiring more effort in maintaining data for a much longer amount of time. Not only are businesses overflowing with large quantities of data but now must solve the issue of, where can all of this data be stored. Rossi provides the example of large credit card companies. In the past, they were required to keep the data records of all credit card transactions for seven years. But now there has been recent talk of extending that to 10 or possibly more years.

Data planning can have a big positive impact on a company as a whole, but planning is essential to success.  The proper planning ensures that things such as cloud storage and prioritizing levels of data for storage within one’s network are all properly set up. Planning out the process and details for proper employee data access is crucial, too. It is important to figure out the limits and accessibility of data for all employees early on to ensure a positive work flow.

So, is it time to take a step back to re-evaluate just how effectively you are managing your data? What plan do you have in place and more importantly, has there been a positive impact on your business?

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6 Things to Help you Tackle IoT and Big Data

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So, you have made the decision to dive into the world of IoT and Big Data? Where to start is the major question and can seem overwhelming. Preston Gralla has come up with some key steps in making the decision or updating your current solution program in his article, 6 Tips for Working with IoT and Big Data.

  1. The first clear way to dive in is to know the problem you are facing and what the end result looks like to you. Without a crystal clear picture of what you have to solve, a project can easily head in a different direction or take longer than expected to go into implementation.
  2. Then, you must deploy the “right people” on the project. Gralla states that Data scientists can be expensive to employ and hard to come by, because, today, they are so much in demand. Instead he suggests that you seek the resources within your company. Employees with the Big Data and IT experience may have the drive and motivation to learn new techniques in order to take on new projects.
  3. Next, Gralla talks about how important it is to know exactly which data you will collect and also how it will be stored. In order to get the most from your analytics, it is important to be working with precise data that will give you the most accurate results and ROI.
  4. Data can be made up of complex layers and other times, it can be a simple layer of information. To ensure that it will work compatibly with each other, Gralla suggests that businesses build an extra abstract layer to allow room for extra layers of data that you may encounter along the way.
  5. The fifth tip that Gralla suggests, has to do with the platform. A large data analytic platforms can be very expensive and take extra time to develop. It may be the most efficient to invest in an outside platform for analytics and even maybe a cloud-based system.
  6. And finally, the last bit of advice when tackling Iot and Big Data is to start with a manageable size and continue to grow from there. Many businesses will take on too much at one time and struggle to succeed at them. Instead, start small so that you can manage to smooth out any errors along the way before taking on more.

To read the whole article, click here.

Healthcare and Big Data are Not Slowing Down

Doctor sitting at office desk and working on his laptop with medical equipment all around top view

The days of paper charting medical records are long gone. Michael Morrison gives a good look into why Big Data is vital to the Healthcare industry in his post, “Big Data Remains Hot in Health Care.”

Medical firms did not have much choice in adapting to these changes after the Health Information Technology for Economic and Clinical Health Act in the US in 2009 took effect, this was one of the largest efforts ever in improving patient care, ensuring proficient operations, and closing the gap of medical error. The result has been phenomenal and continues to progress.

With the ability of the medical industry to continuously run analytics, they gain critical information from high volumes of medical records and data. Morrison mentions that with advancements in patient data analytics, it is becoming the most important aspect of implementing medical analysis, which allows for patient care to be personalized. Many common road blocks that are normal in the course of  patient care and health management can be corrected with the use of Big Data tools.

The National Cancer Institute has created a Big Data project that has, through Big Data research, improved cancer treatments. They are now able to learn a lot about the patient’s responses to different medications and choose the best treatment course for a specific patient. The implementation of data solutions across the entire medical industry benefits everyone involved from the provider to the patient. The next time you make a visit to your local doctor’s office or hospital, take a look around and notice how much we rely on the ongoing advances of technology. Where would be now without all of it; how much safer has it made our treatment as well as our loved ones?

Click here to read entire article.