Human Resources is beginning to pull ahead in the Business Analytics world. One thing is certain, if you want to run a successful business, you need to hire the right people to help you get there. Who is in charge of recruiting and hiring your team members? “DING, DING, DING!” you guessed it, Human Resources. In a “Big Data” world, HR can use “People Data” to their advantage and help businesses develop strategy when it comes to hiring the best candidates. As David Klobucher writes in his article, “Data-driven confidence will help HR professionals identify behaviors and interview styles that attract better employees, as well as qualities that make effective workers – and lead to faster promotions.”
I agree with Klobucher, this is a great time to be in HR. There are big opportunities that may be presented to anyone working in HR. Executives within businesses are looking to their Human Resources department to help build the strategy to success. Of course this all depends on if HR professionals “welcome” the business analytics technology with warm arms. As stated in the article, many individuals working with Human Resources are not completely comfortable using data just yet. In today’s world, Big Data surrounds all of us, but for HR, this can lead to big success from analyzing data of past successes and past failures.
In some HR departments, to take on this scope of technology could be intimidating, however like one of my favorite sayings goes, “I never said it would be easy, I only said it would be worth it.”
Read original article here.
Originally posted on October 26, 2015.
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.
Who doesn’t want the largest return on their investment? The article written by Chris Twogood, How To Produce Ongoing Returns With Big Data, compares current Data and Analytics systems to what he claims is actually needed in today’s businesses.
He writes, and we agree, that Data within companies only continues to grow in volume and variety. Data solutions are developed to handle one issue at a time, which causes data to remain separated and replicated over-and-over again. It’s a prime example of a short term or one-off solution, and it can’t be the best way, right?
Twogood explains, the solution is to implement a sustainable, central data and analytics model that can ensure calculation of vital analyses. Because action and decision begin with the same question…What does the data tell us?
In this article, what stood out to me and truly symbolized what PARIS Tech, the sponsor of OLAP.com, is all about: “To satisfy the individual requests of the organization, an analyst or end user should be able to access data at any time to apply the analytics available.”
PARIS Tech makes it possible for organizations to share an analytical data model in real-time from different applications. Because, like Twogood says, users need to be able to access data at any time, and even real-time. With this concept front-and-center, organizations can see:
- A reduction in time to meet new needs
- Less complexity and cost of infrastructure
- Higher productivity
Click here to read the full article.
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- The Only Constant? Change: Every thing is constantly changing and evolving so this will continue to test your BI deployment at all times.
- 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.
- 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.
- 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.
- 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.
Let’s take a look into some reasons that business intelligence projects tend to fail.
James Haight of Blue Hill Research recently wrote a blog post that breaks down the costs and numbers of Data Preperation. Typical reports focus on hours and efficiency. As stated by James Haight, “At Blue Hill, we recently published a benchmark report in which we made the case that dedicated data preparation solutions can produce significant efficiency gains over traditional methods such as custom scripts or Microsoft Excel.”
According to their study, data analysts spend on average about 2 hours per/day just on data preparation alone. When Blue Hill Research factored in the average salary that a data analyst makes in the U.S., it comes out to be around $62,000 per year. After doing the rough calculations, they figured out that 28% of a data analyst’s time is spent preparing data, which equals about $22,000 worth of their yearly salary. While that number seems high just considering one analyst, you can imagine how drastic that number looks when you figure in how many data analysts there can be at larger corporations. In this post, they breakdown the numbers even more. For example, say a company has 50 data analysts which is estimated that $1,100,000 is spent annually just on preparing data.
In order for data analysts to shift their full attention to where it should be, “analyzing the actual data”, there needs to be a solution implemented. PARIS Technologies has the solution. PowerOLAP is a software that was designed to take the stress and time out of preparing and comparing data. It has the capability to aggregate information from any source into a multidimensional PowerOLAP database. It empowers users the flexibility to slice and dice with ease. Learn more about how PowerOLAP could be the solution for your company facing this problem.
To read the Blue Hill Research post, click here.
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?
Want to read the entire article? Click Here.
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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.
What does December 18th, 2015 mean to you? Ok yes, it is one week before Christmas but if you are a Star Wars fan, then you know it means much more than that. The awaited release of “The Force Awakens” has caught quite the buzz around this holiday season. Jim Hopkins does an awesome job at bringing Star Wars and Business Data/Analytics side by side in his article: How Star Wars Can Help with Your Data Problems.
If you are new to Business Intelligence terms such as CRM, Big Data, Analytics, this article does a good job of laying it out clearly.
Hopkins first relates “the Force” to “the Data” in the business world. “The Force” is an abstract power that connects them and controls their world. Which is incredibly similar to “the Data”. What would we be without data? What would we analyze to gain crucial insight on the decisions that are made to strengthen our businesses? The same analogy holds true for businesses’ CRM systems. The CRM (Customer Relationship Management) connects everyone from Marketing, Sales, Finance, Support and Administration.
This leads into Hopkins’ next comparison: “The Dark Side”. Without the proper care and management of a CRM system, it can quickly turn “dark” as Hopkins puts it. Collecting large amounts of useful data is a great thing, having the ability to store and organize this information is also a great thing. However, without close attention to detail many businesses can allow their knowledge of information to turn sour. It is a crucial part to the success of a company, to pay attention to detail and making sure what is being stored is accurate. What is meant to strengthen and prosper a business, can quickly do the opposite if not properly maintained.
When Luke Skywalker is attracted to the Jedi lifestyle, he begins to gain greater knowledge of his father’s past, a Jedi master. Through this, he is able to strengthen the power he holds within himself. In the business world, we must truly understand what our goals are and how our decisions are impacting them. When we run analysis reports, what patterns do we see? What story is the data telling us?
As Darth Vader said about Luke Skywalker, “the force is strong with this one.” Hopkins relates this to having a strong set of policies and mechanisms in place when implementing any data analytic strategy or program. Everyone must be on the same page and follow the same guidelines to ensure the highest quality of data outcome within a business.
Click Here to read entire article.