A company’s data warehouse has minimal benefits without analytics apps to extract business insights from raw data discovery. This is why platforms like Knime, Qlik, Aws, and IBM’s cloud PAK are becoming popular. But why are analytic platforms beneficial? Continue reading for all the answers.
Making efficient decisions in business is what keeps the production and income streams ticking. Business leaders (before the era of computers and the internet) had quite a hard time making data-driven decisions. The data was just not there, or there were not many analytics resources to harness data for businesses. Today, the world is at the feet of businesses that favor deep learning in their decision-making.
But how do analytics platforms help on this front? Analytic platforms offer two primary features: predictive and prescriptive analytics. Predictive analytics involves machine learning techniques like simulation to forecast business outcomes. After forecasting, companies of all sizes can then use prescriptive analytics in deploying the intelligence generated. With visual modeling, businesses can create several options that can help solve existing or future challenges in different scenarios. The final result is the company opting for the best decision with the help of an interactive dashboard.
Marketing involves finding customers’ needs and tailoring offers. Interpreting customer behavior and demands of users need to be accurate. Or else you might be building an entire organization’s marketing strategy on a wrong footing. It also involves looking out for new opportunities for your salesforce to make their bids with less friction.
All these marketing needs are attributes of efficient analytics platforms. When all insights from social media and other channels come together, businesses can determine which campaigns generate the most leads and which actions have the highest churn rates.
Many businesses like to think of their client relationships as forever. But nothing can last long if the value doesn’t go both sides of the coin. This is especially true with a customer 4.0 who can find options with one Google query. The best way for businesses to carve meaningful relationships with clients is to listen attentively. By listening, a company can understand customers deeply and determine areas to improve.
Businesses can create personas to deconstruct generalized marketing into personalized touchpoints using algorithms that legally feed on customer data. With a data analytics platform, a company can turn its customer experience up a notch and enjoy repetitive transactions from business users.
Every move in a modern operational environment leads to many bytes of data. Whether it’s taking stock of a warehouse’s remaining inputs or managing maintenance routines in a garage. All these are relevant data required to automate business processes.
Data analysis can impact operational efficiency a great deal. With actionable insights from analytics tools, businesses can quickly identify breaks in a workflow. An analytics solution can also help run operations research using a business’s historical data from multiple data sources, including SQL. After searching through tons of unstructured and structured data, your company’s analytics platform can tell whether there has been operational progress or not.
The COVID-19 pandemic came with a new set of realities for many businesses. As companies strive to scale some of these challenges for a post-pandemic world, agility has become even more essential; but, exactly what is agility? Well, it’s a term rooted in data science and data management disciplines. It involves the use of big data in responding to challenges as and when they arise.
No challenge has ever announced its coming. And you’re right if you say challenges won’t wait for you to prepare before doing harm. The only way is to have an agile structure and culture at your workplace that enhances security and encourages innovation for resilience.