We live in a decade that states changes in the concept of economy, business, medical sciences, and technology. With all the new prospects we are now focused on there are many new minds and businesses that are coming forth as start-ups or those already established are changing the policies with the time.
Every day we make a decision as a businessman or an employee for a better world and each decision has its own importance. Decision making involves the analysis of a defined set of alternatives against some selective criteria. These criteria usually include cost, benefits, pros, cons, and preferences. This allows us to analyze from the data that are handy for the development.
We can’t expect to make a ship without knowing the property of buoyancy. Trying to do so would just be a plan to make it sink.
The idea is not only about running a business for a long time but also letting the concept change and develop with the time. A business changes drastically when it gets an interference. An interference to see the data differently, play with it, get useful insights, make future decisions, and predict the future.
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There is a question- who will dare to interfere?
“We do. Though we share some common responsibilities, techniques and goals but with a different skill set and expected outputs generated with business data,” says Data analyst and Data scientist.
On a daily basis, the world generates close to 2.5 quintillion bytes of data. Each company generates a large amount of data and a pool of questions emerges with each addition.
Businesses need answers to questions such as “Which of the products is performing best in terms of sales total?”, “Who is the best employee of the month?”, “Which demographic sector is busy in buying more and more of our products?” and “What will be my future sales trend?”.
Roles to Understand
BI analyst is a profile that carries such knowledge. The person given the role understands the business requirement. He talks to the owner of the company and gets information on the insights he wants to drive. BI Analyst’s main task is to find patterns and trends in your business’s historical data. What stories do the numbers tell? What business decisions can be made based on these insights?
That makes BI largely an exploration of past trends. BI analyst is good in excel, also use SQL to pool data, clean some transformation and use enterprise BI tools such as Tableau or Power BI to generate the dashboard or visualization and the reports which can give insights on the business. Mastery of the visual presentation of information helps with speed bottlenecks on the brain side.
Beautiful and effective charts and diagrams allow the mind to gather information faster and gaining potential insights. This person works closely with the business manager, CEO, or CIO of the company and creates dashboards as per the requirements of those stakeholders.
BI analysts can answer the first three questions as it can be driven from data by analyzing it but the last one is based on predictive analysis, others can be like there will be maximum customer traffic, in simple terms predict demand, price, risk and many more based on the business domain. Predictive analysis needs advanced machine learning and deep learning to build models that can do this job and for this data, scientists came into the picture. Data Scientist has to work closely with the application developer and will integrate the model with enterprise software so in this way, he also contributes to the software development process as well.
A Data Scientist will predict the future for your various criteria with an accuracy rate chart and evidence. With the coding chops and stubbornness, build a machine learning model to identify relationships between features like average order value and customer age in order to predict the outcomes like how much a certain customer is likely to spend that passes testing at 99% accuracy. The specialist knows they won’t get the perfect solution in books instead they have to run in a marathon of trial and error until their urge to win is satisfying.
A misconception
Well, where predictive analysis is concerned, a data scientist might be a person who can make a model with higher accuracy but he or she cannot guarantee the actual results
“There’s no magic that makes certainty out of uncertainty. There’s no profile with perfection and no business without a hurdle.”
Good analysts and scientists have an unwavering respect for the one golden rule of their profession: “do not come to conclusions beyond the data”. These peddle nonsense, leaping beyond the data in undisciplined ways to support decisions based on wishful thinking. So that lies in the first place, data always lies in the hands of BI analysts and data scientists.
With the upgrade in technologies and data structures, the hybrid of analyst and machine learning will bring the best to you. Analyst accelerates machine learning projects, so these dual skills are very useful. Machine learning projects can be given a new height with Business Intelligence like a proper POWER BI tool to express your outcomes in various different views that may accelerate the level of analytics.
The punchline
“A perfect tool for high analytics is the sprinter, with the ability to quickly help you see and summarize what-is-here is a superpower for your process”
Big Data has transformed the industry. Companies are in need of BI Analyst and Data Scientists more than ever. Both have their own excellence but a BI Analyst brings speed and Data scientists with performance. Both parties are ultimately valuable and complementary.
The data aggregation and transformation BI analysts conduct puts data into a format that data scientists can easily repurpose when building models, find patterns, design experiments, and share results of the data with the team in an easily digestible format. If you lose your analyst and scientist, who will help you figure out which problems are worth solving, who will help you to take the right step for your future project?
