Software Engineering Insights

Customer Relationship Management (CRM) is a tool that serves as the single source of truth for all your organizational data while enabling sales teams to drive better performance. Bad CRM data, if utilized for your business initiatives, can cost your organization severely in terms of client relationships, loss of the market base, and ultimately, sales revenue.

Your organization's sales team deals with large stores of data around customers and prospects captured in your Customer Relationship Management (CRM) system. Say your customer changes their role in their organization, their contact details, or other aspects of their profile - their data in your CRM can become stale if not updated and enriched periodically.

Customer experience is a core focus area for businesses today. The perception of your brand or organization is an essential differentiator to achieving ideal outcomes in today's customer-centric business landscape. Accordingly, only with Customer Relationship Management (CRM) software that ensures efficient Customer Experience Management (CXM) can you build a brand or enterprise holistically.

The operational and infrastructural overhead involved in running and maintaining cloud-based solutions is often massive. There is considerable effort and expenditure in the construction and scaling of storage systems for tons of user metadata and other in-house files. Dropbox, the file hosting pioneer, is a success story about how cloud costs can be minimized by intelligently managing your infrastructure.

The automation of time-consuming tasks involved in marketing campaigns using Customer Relationship Management (CRM) software is an emerging trend. In particular, there has been an increase in the adoption of Salesforce for marketing automation because the resultant benefits far outweigh the associated costs and efforts involved in its integration.

Rolling out a new software system, infrastructure, or technology solution for an industry such as healthcare or personal finance has critical end-user outcomes. Technology Readiness Levels (TRL) refers to a robust scale often used by pioneering software organizations throughout their development efforts.

PyTorch and TensorFlow are two of the most widely relied-upon frameworks for Deep Learning (DL) research and industry implementation. While both these DL development frameworks haven't been around too long, they have made a significant mark in AI/ML research and innovation.  However, when it comes to which between PyTorch and TensorFlow is the better framework, there has not been a clear consensus.

Big data adoption is increasing rapidly across organizations of all sizes. However, the method and distinction between obtaining Business Intelligence (BI) and employing Data Analytics (DA) to make actual business decisions with an impact are getting lost in translation. While both terms are used interchangeably, BI and DA are essentially distinct in many ways.

Businesses around the world spend billions of dollars every year on cloud infrastructure services, storage, and computing resources. They can gain an edge over each other with effective cloud infrastructure without any wasteful cloud spending. There are two rising approaches towards cloud cost optimization today that they can choose from; Capital Expenditure (CapEx) and Operational Expenditure (OpEx).

The healthcare systems market has witnessed a large-scale shift towards more patient-centered care models in the recent past. The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) is one of the most reliable ways to measure patient satisfaction which can help digital patient-facing and patient-monitoring doctors' apps meet leading market standards.