Distinguishing Business Analytics and Business Intelligence

As the fields of business intelligence and business analytics continue to develop and grow, organizations must be aware of the distinctions between the terms and understand their value. Adoption and usage of business intelligence and analytics tools show no sign of slowing. Understanding these concepts is vital to making the best business decisions, to maintaining a competitive edge across all industries, and to enabling companies to capture operational and strategic value.

To learn more, see the infographic below created by Pepperdine University’s Online MBA program.

Distinguishing Business Analytics and Business Intelligence

Distinguishing Business Analytics and Business Intelligence – Resource from Pepperdine University

Differences Between Business Analytics and Business Intelligence

The goal of business analytics is to develop successful analysis models. It simulates scenarios to predict future conditions. It is a very technical approach to predict upcoming trends. This process helps find patterns after analyzing previous and current data. The analysis is used to devise future courses of action. Professionals working in this field use data mining, descriptive modeling, and simulations.

Business intelligence uses different types of software applications to analyze raw data. Professionals working in this field study business information. They closely consult with decision-making managers. They identify existing business problems and analyze past and present data to determine performance quality. They use KPIs and other metrics, and prepare easy-to-read reports. The reports give unique insights into the workings of the business and empower organizations to make optimum business decisions.

Business analytics experts help predict what is going to happen in the future. They use data to analyze what will happen under certain specific conditions. They can predict the next trends and outcomes.

Business intelligence experts, on the other hand, help track and monitor data and business metrics. They can correctly identify what happened and what is happening now. They can discover why something happened, how many times something happened, and when all such events took place.

Data-Focused Talent Shortage

Very few managers have high expertise in data fields because the use and analysis of big data has emerged only in the last few years. Even new managers and leaders do not have requisite skills to devise data-driven digital strategies. Most organizations need a new kind of talent base that is well versed in the data-driven business landscape. One McKinsey report estimates that by 2018, the US will face a shortage of 140,000–190,000 data science professionals. Even now, companies must pay very high salaries to employ data analysts. Only large companies can afford such professionals.

The Future of Big Data Analytics

While 78% companies agree that big data will impact their business, only 58% think their company is ready to take advantage of all the potential that big data offers. The reason for this is not difficult to ascertain. Companies must use various techniques to capture data, and the data collected must be realized in a specific format. Data analysts must use exacting methods and processes to analyze this data. Capturing and analyzing big data is a complex process and can be handled only by trained data analysts.

Benefits of Business Analytics

Engaging effective business analytics is necessary to make the right business decisions. Managers with proven analytics skills are better able to plan for future projects. The biggest advantage involves forecasting. Analysis of previous and current data helps predict future trends. This information is crucial to the success of a business. A company may have different types of products. It may keep promoting the fast-selling product while another product that is quickly gaining traction may remain under the radar. Only big data analysis can reveal the importance of the latter product. Business analytics is a forward-thinking way to improve operational efficiency. Decisions can be made faster, and it becomes easier to make sense of large volumes of data.

Benefits of Business Intelligence

Business intelligence proves useful in identifying new opportunities. A company can identify a new market that holds important business opportunities. Product pricing can be tweaked to market demands. Business productivity can be improved. Sales and marketing expenses can be optimized. Business intelligence helps predict customer behavior, which proves useful in improving customer service.

Usage and Adoption of Big Data

Even when the benefits are well known, very few companies are able to use big data analysis in a significant way. Almost 50% of businesses face difficulty in the field of business analytics. They are unable to ensure the quality of data. Without the right talent to manage and analyze data, they are at a disadvantage in the market. Many businesses rely on simple applications to analyze data. These tools are not very effective in analyzing big data. This type of data must be analyzed scientifically. It is a complex job that can be handled only by professionals who possess training and skills in data analytics.

Developing a Big Data Analytics Culture

All types of businesses are working continuously to take advantage of big data. They are using simple as well as complex solutions to work with such data. There is a consensus realization that a high level of data analytics is necessary to ensure business success in today’s market. Now, companies are incorporating data analytics into all their departments. They are using sophisticated tools and solutions to predict future trends. Almost 82% of business executives now take advantage of data-driven reports and dashboards.

Sources of Big Data

Big data is obtained from a wide range of sources. Sales records and financial transactions generate a great volume of useful data. They help devise pricing models for different types of products. The customer database is a key source of data. Large amounts of contact details and other data can be mined from emails, productivity and communication applications. In fact, every business process generates data. All such data must be collected and stored properly.

Businesses need the services of both business analytics and business intelligence experts. There are differences in their positions, but both groups play important roles in the success of a business. As more and more businesses rely on digital strategies, they have to analyze their big data properly and effectively. They need the support of trained and skilled data analysts to help achieve the best business success possible.

 

Infographic: Business Analyst vs. Data Scientist

Business Analytics vs. Data Science

“Business analytics” and “data science” — are they basically interchangeable terms, or entirely separate professional pursuits? There’s certainly overlap on the topic of Big Data and using data to inform decisions. There is no dispute over the fact that both business analysts and data scientists use exponentially growing sources of data to do their work. [Check out PARIS Tech’s recent post on Big Data]

An article and featured infographic by Angela Guess for Dataversity.net argues that the terms business intelligence and data scientist are distinct, and not just because one pursuit applies to business, and the other to scientific results.

infographic-business-analyst-vs-data-science

Click below to read the original article which accompanies the business intelligence vs. data scientist infographic.

Infographic: Business Analytics v. Data Science

 

[Infographic] Business Analytics : The Intersection of Science and Business

What is Business Analytics?

Science and business continue to intersect, most recently on the topic of data analytics. Generally speaking, “data analytics” is the process of organizing and interpreting data to uncover valuable information. “Business [data] analytics” is the more specific application of data analytics to business purposes.

Some examples of data analytics might be: What segment of customers use desktop v. mobile? Or, which target audience found value in the most recent advertising campaign? Companies ranging from Target to Google find results from these kinds of questions so valuable that they pay data analysts over $100,000 per year. To learn more about the burgeoning data analytics industry, check out this educational resource, created by Villanova University’s Master of Science in Analytics program.

Infographic-Business-Analyticshttp://taxandbusinessonline.villanova.edu/resources-business/infographic-business/the-intersection-of-science-and-business.html

Excel is Not a one Stop Shop for your Data Needs

Excel, not a one stop shop

“There’s nothing inherently wrong with spreadsheets; they’re excellent tools for many different jobs. But data visualization and data communication is not one of them.” – Bernard Marr

We couldn’t agree more with what Bernard is saying in his article, “Why You Must STOP Reporting Data in Excel!” Excel is everywhere and it has proven to be a valuable resource to every company across the globe. The problem is that many companies are using spreadsheets as their main line of communication internally. Excel is great at displaying all of the raw data you could possibly dream of, just ask any Data Analyst, who eats, sleeps and dreams of never-ending spreadsheets. Bernard gets right to the point and lays out the top 4 reasons that spreadsheets are not the right fit for visualizing data and communication within an organization.

Most people don’t like them.

Bernard makes a great point, unless you work with Excel frequently like a data analyst, it has the reputation of being intimidating. Employees will be reluctant to use it, let alone even think about analyzing data from it. If employees are not clerking in Excel all day, they are most likely going to give Excel the cold shoulder when it comes to communicating data.

Important data is hidden.

I think it is safe to agree with Bernard on this. Spreadsheets are not the best visualization tool out there. Most spreadsheets today are full of endless numbers. If users can’t look at the data and quickly decipher valuable vs. non-valuable, that is a problem. There are better visualization tools that paint a clearer picture and allow for effective communication.

Loss of historical data.

Users in Excel are constantly updating the facts and data as necessary. The downfall to that is it essentially erases all historical data. Without historical data there is no clear way to see the trends and patterns. It takes away the ability to make predictions for the future.

It’s difficult to share.

Spreadsheets are not ideal for collaborative data sharing because they allow the risk of having data deleted or changed. The way that data is shared today is by emailing updated spreadsheets. This data is considered stale or dead, it lacks the key component of remaining “live” or in real-time. This way of sharing is not only time consuming but eliminates the opportunity for users to collaborate while never losing connection to the most updated information available.

The great news is, there’s an easy answer to all of the common frustrations of spreadsheets…

PowerOLAP is an example of a product developed with a solution that addresses all of these problems. It allows for real-time collaboration between users, while always remaining “live”. It has the ability to store historical data which allows for accurate analytical predictions to be reported. Take a deeper look into PowerOLAP and see how it can take your organization to the next level.

To read the entire article by Bernard Marr, click here.

 

Human Resources, Making BIG Strides in Business Analytics

Business Analytics

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.

How to get the Largest Return from your Big Data

 

Businessman drawing ROI (return on investment) with graphs

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.