Data Science vs Business Intelligence Difference Between Data Science and Business Intelligence
Data Science vs Business Intelligence: Difference Between Data Science and Business Intelligence
If there’s one thing that’s common to most sectors of the fashionable industry, it's Big Data. While data is that the new currency of the 21st century, experts who can effectively leverage Big Data are invaluable assets of companies and organizations. Data Scientists and Business Intelligence (BI) professionals are two such valued assets for companies since they will extract meaningful insights from data to assist boost profits and gain the whip hand over competitors.
Yes, Data Scientists and BI Analysts both work closely to rework data into business-ready insights which will create value for a business. They aim to make favourable business outcomes like boosting ROI, expanding brand reach, enhancing customer satisfaction, customer retention, and so on. In other words, Data Scientists and BI Analysts help add up out of massive Data by delivering competitive intelligence or data-rich insights.
But then, does it mean these two roles are the same?
No, they aren’t the same.
Although Data Science and Business Intelligence are related fields that specialise in churning value out of massive Data, they need a good share of differences. Today, we’ll deep dive into those differences to raised understand the 2 inter-related fields – Data Science and Business Intelligence.
Data Science vs. Business Intelligence: What Do They Mean?
At its core, Data Science is all about studying, analyzing, and interpreting voluminous data to get the hidden insights from within by combining interdisciplinary sciences like Mathematics, Statistics, computing , and knowledge Science. Thus, Data Science analyzes past data trends to form data-driven future predictions. Business Intelligence, on the opposite hand, refers to the suite of technologies and methods a corporation uses to research business data.
Data Science vs. Business Intelligence: What are The Major Differences?
Data Science is that the game-changer of the 21st century. it's completely transformed that way businesses handle data. Earlier, BI was largely a manual domain, monitored and performed by IT professionals. However, today, because of Data Science technologies, most of BI and Data Analytics operations are automated – business data is stored in centralized data repositories from where data experts can extract insights and intelligence using automated tools, as and when required. during this way, Data Science has brought the core BI and Analytics operations to the forefront of the business canvas.
Here are 6 pointers highlighting the difference between Data Science and Business Intelligence:
1. Focus & Perspective
Like we mentioned earlier, Data Science is meant to peek into the longer term . It interprets the past and present data to see what the longer term of a corporation will appear as if . Contrary to the present , BI looks backwards on historical to deliver detailed reports, KPIs, and trends. However, unlike Data Science, BI doesn't depict what the insights might appear as if within the future through adequate visualization.
While Data Science is all about exploring the depths of business data and experimenting with the insights in many possible ways, traditional BI systems are static, therein they are doing not provide the scope to explore and experiment with how a company collects and handles the data.
3. Data Handling
BI is made to research and interpret highly structured and static data, but Data Science supports high-speed, high-volume, and multi-structured complex data gathered from disparate sources. While BI is meant to know only pre-formatted data in specific formats, Data Science technologies can effectively collect, clean, process, analyze, interpret, and visualize free-form data collected from multiple sources.
4. Data Storage
The present business scenario is extremely dynamic. New trends, new technologies, and new methodologies constantly shape the industry as we speak. Thus, it's crucial that data, like all other enterprise asset, is flexible enough to sync with the fast-paced industry trends. this is often where Data Science take the whip hand over BI – while BI systems store data in siloed in data warehouses (making it difficult to deploy across the business infrastructure), Data Science takes the central repository approach to assist move data in real-time.
5. Business Focus
Data Science and BI differ in how they deliver value to a business. Business Intelligence analyzes historical and present data to seek out out answers to the questions that are already on the table. However, Data Science digs into large and sophisticated datasets to get new and innovative questions that you simply didn't know existed. during this way, Data Science encourages businesses to explore new opportunities, domains, and challenges with data insights.
6. IT-Owned vs Business-Owned
Previously, BI tools and systems were mainly controlled and managed by the IT department who extracted the intelligence manually then forwarded it to data analysts for further interpretation. Data Science has changed this approach by collating all related actions simultaneously. Data Science solutions and technologies are operated by data analysts, data scientists, and BI specialists who can specialise in analyzing data to make actionable business predictions rather than committing their time to “IT housekeeping.”
Data Scientists vs. BI Analysts
By now it must be clear to you that Data Scientists and BI analysts are two different roles within an organization. While the previous focuses on extrapolating past data to assist companies mitigate potential business risks and challenges within the future, the latter focuses on interpreting past data to seek out answers to immediate questions and business challenges. Hence, Data Scientists and BI analysts both work hand-in-hand to equip companies with data-driven insights and help them to be prepared for this and future business scenarios. What unites Data Scientists and BI Analysts is their love and affinity towards data analysis. Both experts use advanced algorithms, tools, and frameworks in several capacities and degrees to empower companies with fact-based and highly accurate insights which will make or break a business. Since Data Science and Business Intelligence are hot and trending fields within the industry immediately , it pays extremely well to create Data Science and BI skills. And what’s better than enrolling during a certification course to develop industry-specific skills?