Our team of data analysts and scientists constantly explore various packagaes and
databases and can advice on the optimal combinations.
Whirldata understands the power of using the right approach to extract relevant insights from an accruing pile of data. It has been known and accepted for the last several years that Business analytics and business intelligence solutions can help improve the decision-making capabilities of organizations, cut costs and identify new business opportunities.
In addition, with many organizations starting to explore and deploy Machine Learning based solutions, Data Analytics as a field of offering has taken on a more important role as the first step in the development of any Machine Learning system is the ability to visualize existing data. The right kind of visualization significantly impacts the performance and accuracy of ML systems.
Data Analytics, hence, is critical from two aspects – one by itself and another by ensuring that expensive and powerful ML systems that are built perform optimally when deployed. So any effort at building and deploying analytical tools/solutions requires the in-depth understanding of the business drivers that have led an organization to consider the possibility of expanding the use of data analytics tools/solutions.
We, at Whirldata, always begin all our engagement with our valuable customers by delving into the underlying business case and then employ the use of the right tools/packages or custom-build a new one from scratch. We look upon every engagement as a consulting engagement irrespective of what the commercial models maybe and ensure that we impart as much value in the development/deployment process.
Once have a good insight of the business case, we choose the right tool/combinations of tools/custom build solutions for Data Gathering, Cleansing, Integrating, Analyzing, Presenting and sharing of data. Our team of data analysts and scientists constantly explore various packagaes and databases and can advice on the optimal combinations.
A few of our capabilities include:
Development using statistical and numerical packages in Python