Notes

How data can aid in the development of a successful Digital Transformation strategy

More than ever before, digital transformation is the talk of the town. Despite the hurried initiatives and fast adoption of digital solutions in response to the pandemic's situational concerns, data remains a persistent aspect that must be considered. No amount of money can guarantee the success of digital transformation programs without data, exceptionally high-quality data.

Data is at the heart of digital change.

Technology, data, process, and organizational change are all part of digital transformation. The word "digital transformation" is so broad that it varies from store to store. But I believe one thing that resonates, regardless of where you're doing it or what it means for your company, is that it will be based on data. You can't alter it digitally until you have data. So, one of the things we've brought here is an Enterprise Information Management strategy and plan, which means we'll start by corralling all of the data.

The transition from ETL to ELT testing

ETL is the process of taking data from a source, converting it to the desired format, and then loading it into a single repository. During the three Extract, Transform, and Load processes, ETL testing checks, verifies and qualifies data while preventing data duplication and loss.

Getting the right balance between transformation plan and digital technology

Nothing has ever been able to accelerate the digital transformation path as much as this continuous pandemic. To maintain company continuity, strategies were overturned overnight, and transformation efforts were immediately put into action. As a result, all of these are now influenced by the digital transition. That's what we're seeing with major enterprises using various tools to achieve it. Today, the most significant problem, in my opinion, is gaining access to the necessary skill set. The digital transformation tsunami appeared out of nowhere. More skilled workers are required, as well as more instruments to aid in the transformation.

Bridging the gap between digital strategy and customer service effect

Customer service is unquestionably crucial, as this pandemic has taught us. It hasn't vanished. It's even more relevant now. We must be thoroughly knowledgeable about our goods and service. We should understand what we're offering, speak about it, and have SME or subject matter experts deal with our internal customers so that they can respond quickly if they need assistance.

Impact of developing technologies on testing and quality assurance

As a result, you'll require a lot of data. Regardless of whether you use ETL or ELT, you must check the data in both scenarios. You must ensure that the data quality, compliance, and security requirements are all met. Only via quality assurance and testing will you be able to accomplish all of them. Testing is now referred to as quality engineering, and it is integrated into your lifecycle from the start.

To summarize

Data processing and cleanup can take up to half of an analytics team's work, even for highly compensated data scientists, limiting scalability and frustrating personnel. Employee productivity can be harmed across the board: Because of poor data quality and availability, respondents to our 2019 Global Data Transformation Survey said they spent an average of 30% of their total enterprise time on non-value-added tasks.

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