Enterprise Resource Management (ERP) software. Business professionals have heard of it, but they may not understand how it can help their business. In short, an ERP gathers data from multiple departments, including accounting, human resources, sales and marketing, and inventory, into a central database. This database then allows members of management and other key employees to analyze their current processes, spot workflow weaknesses, and improve them.

Soft skills can be almost as important as data engineering skills when you apply for a job. Soft skills can make the difference between stress and efficiency or being unsatisfied with your position and a raise. When data engineers and data scientists earn bachelor’s degrees, they usually take classes in topics like data warehousing, programming languages, machine learning, and data science.

With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.

The software industry is undergoing numerous changes with the growth and advancement in technology and the emergence of Agile and DevOps. Software testing has slowly transitioned from manual testing to record-and-playback testing to automated testing, and now codeless testing is disrupting the software testing approach in the industry. The codeless automated testing involves the execution of automated testing without using any script.

Times have surely changed — we’ve all moved on from TVs to mobile phones and laptops to consume various forms of content. As per Data Reportal, there are over 5.27 billion mobile users globally, and this data also reports that the number of users is increasing by 1.9% per year; the internet users are increasing at an annual growth of 7½%, especially in the developing countries.

What do Google’s DevOps Research and Assessment (DORA) and Rollbar have to do with each other? DORA identified four key metrics to measure DevOps performance and identified four levels of DevOps performance from Low to Elite. One way for a team to become an Elite DevOps performer is by focusing on Continuous Code Improvement.

Analyzing Return User Behaviour helps you optimize your site for better engagement and more conversions.

A true service mesh should focus on how to manage and orchestrate connectivity globally. Connecting a new service mesh for each use case is a much simpler problem to solve, but doing so won’t help you scale. You’ll just be throwing a service mesh in each cluster and calling it a day.  The more appealing solution is to stitch together environments.

A revolution is transforming organizations and it's driven by low-code. Using low-code, organizations can quickly build—even in only a few weeks—enterprise applications that would once have taken months to get off the ground. Forrester predicts that by the end of 2021, 75% of development shops will use low-code platforms (up from just 44% in 2020).[1] With that kind of momentum it’s no wonder the low-code market is exploding.

Data collections and analysis is critical to ongoing business operations, but maintaining data integrity is an often overlooked problem. Ensuring data integrity is not only a consumer trust issue, but is often also mandated by legal regulations. Without accurate data, business leaders could make decisions that are slightly (or majorly) misguided.