According to a top report on business analytics training, companies are hardly making the best use of their analytics. The major difference between a company using analytics and the ones that are not using it lies in the way they hire and train business analysts in the organization. Due to the rapid growth in the demand for real time actionable intelligence, a majority of the top data science companies are asking their employees to pursue the Best business analytics certification. The benefits are many, of which I have mentioned the top 5 here.
- Companies that have trained their business analysts have a faster and agile Go Market strategy
- They are better equipped at predicting the future outcomes of their decisions and actions.
- These business analysts, once trained in data management and data science ops are better equipped at digital transformation workflows.
- Companies become innovative.
- The cost of overall operations eventually comes down due to analysis on risks, efficiency management, and inventory.
According to a report, 90 percent of companies are turning to data science and hiring professionals from top business analytics certification courses to drive their data ops goals. However, only 39% of these companies have actually managed to tap the resources well to proliferate into new markets. Though they have managed to hold on to existing markets, their effort to meet standards in new revenue destinations fails to show results. Only 13 percent of the companies came out openly to state that they have achieved their desired targets — but at the price of hiring at least 2 business analysts in the past 12 to 18 months. Infusing analytics across an organization is a tall task, and business analysts in such small numbers can generate results as per the organization’s development chart.
Despite having hardworking analysts in the team, companies are still way behind their aspirations.
Why is that so?
Unsuitable hiring of business analysts can kill a business faster than a new competitor.
And therefore, the top reason why tech companies lag in their data science aspiration is “unsuitable hiring”. Merely having a business analyst tag in the job profile doesn’t help a professional get close to data science teams. The individual has to be highly motivated and self-driven to understand how the overall team SLAs match and build. Internal stakeholders have to demonstrate and work on their analytics goals, even if it means setting regular meetings and doing hands-on tasks.
Takeaway:
Top business analytics certification course trains individuals in simulated ecosystems where business stakes are just as high as in real scenario — which means, trainees would work in highly aggressive data science environment along with side trainers, customers, and partners.
Not Focusing on Agile Analytics
Agile Analytics is the most progressive data science technique that is making a rapid stride in the business analytics market. However, companies are still lagging in Agile Analytics, turning to raw form data management to satisfy their short-term goals, eventually losing out to a larger paradigm. So what is Agile Analytics?
According to an analyst training provider, Agile Analytics is built on the foundation of flexible data science operations that can be scaled to meet any demand of the organization, short and long-term, or both.
Takeaway:
In the top business analytics training course, trainees are made to work on data discovery models in a more experimental methodology, providing value to the overall process, rather than just focusing on a set process. This strategy helps BI teams to move past the usual rut of biases and data cleaning, which take a bulk of time in BI operations.
Failing to Integrate Data from Different Sources
From a technical point of view, there is another reason why businesses lose their sheen — poor integration platforms. Yes, it’s a challenge to connect all the data points in one place, and expecting that tools would do it for you is a silly proposition. Trained business analysts from certified courses have a handful of knowledge on how to extract data from websites, CRM, social media, email lists, and open source platforms. This can take time — which often runs into weeks, if not months. Therefore, trained analysts work on real time third party and first party data to ensure there is a minimum lag between the hypothesized scenario and the real picture.
Takeaway:
With analytics in agile mode, and focusing on data integration opened new revenue streams for companies that invested heavily in data analytics and BI talent.
