Big Data v/s Business Intelligence!!!
Big data refers to large data sets that exist typically within organizations. Business intelligence refers to the utilization of this data for analytical purposes from which actionable information can be derived to make more informed business decisions. Both of these terms are playing an increasingly large role in business operations today.
Big Data
Big data is best described as the information that organizations store typically in large “sets”, or volumes that is difficult or in many ways impossible for them to leverage in any meaningful way.
An obvious example of big data would be something like the information that is produced through social media channels impressions, click-through rates, engagements; all of these indicators add up together to make up what we consider “big data”.
Growth of Big Data
While the growth of structured data is already a big challenge for organizations to overcome, the rapid growth of unstructured data is presenting a larger point of contention.
Structured data does at least have the benefit of being relatively simple to decipher many businesses already use CRMs for example to analyze customer data more effectively to improve their sales process.
It’s the growth of unstructured data that’s giving companies more pause for thought.
The vast majority of big data is unstructured, and this disparity will only continue into the future.
In fact, unstructured data is growing at a rate of around 55–65% per year.
As a result, leveraging tools to utilize this data is now even more important to businesses as effective use of big data becomes the competitive differentiator between organizations.
Structured and Unstructured Data
Within big data is structured data and unstructured data.
These two different types of information are important in understanding the importance of big data analysis.
Structured data is what you would typically expect to find in formal databases and is often understood as quantitative data.
Structured data will exist in things like spreadsheets, with carefully arranged rows and columns which can be easily read and assessed.
Unstructured data refers to virtually everything else, but can be thought of qualitative in nature.
Examples of this kind of data are videos, images, sensor information, call transcripts, and other forms of informal communication like email body text.
Business Intelligence
Business intelligence refers to digital tools which are used to analyze data, both structured and unstructured, into actionable insights to inform decision making.
For most organizations, business intelligence (BI) will be most familiar in the context of structured data, though advances in the use of AI and machine learning mean that unstructured information is more commonly being deciphered for use
Use of Business Intelligence Within Organizations
It perhaps shouldn’t come as too much of a surprise to learn that many businesses lag behind in their adoption and use of BI tools.
Globally, adoption of BI across all organizations is around 26%.
While over half of all enterprises consider cloud BI to be either “critical” or “very important” to their ongoing and future initiatives, Gartner found that 87% of businesses are considered to have a low level of analytics maturity.
Furthermore, a 2020 executive study found that just 27% of organizations think of their operations as “data-driven”.
So, the present situation is one in which companies understand the importance of using business intelligence for their big data sets, but are showing a low appetite for implementing BI tools into their workflows.
Why should organizations want to adopt BI solutions?
The answer is perfectly simple in that organizations that implement BI start seeing significant positive results for their productivity and bottom line because they are able to put their big data to use through better-informed decision making.
10 Business Intelligence Stats That Show Its Worth
