Systems | Development | Analytics | API | Testing

Modern organizations have multiple touch points continuously collecting customer data. Data collection is essential for firms that use it for personalized marketing campaigns and improving customer experience. Analytics provided by this data help enterprises observe customer behavior and make critical business decisions. However, before firms can explore any use cases, it is crucial for them to recognize the data touch points where vital information is collected.

It’d be hard to find anyone who’d say that taking a data-driven approach to business decisions is not worthwhile. Yet, so many businesses aren’t doing it because, as simple as it may sound on paper, it takes a great deal of strategic planning to pull off. One of the most crucial tools when it comes to accomplishing a data-driven decision-making process is known as ETL.

This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.

The customer journey is the decision-making process each buyer goes through before converting to a paying customer of your business. Mastering this journey will require an in-depth understanding of each stage and how you can continually improve your efforts. To understand this journey, you need to take a customer-centric approach, putting yourself in your customer’s shoes to understand their point of view.

Our five key points: Your data management processes are only as effective as the quality of the data you collate. Gaining access to as much data as possible is vital if you want the business-critical insights that can set you apart from the crowd. For Ecommerce businesses, so many of the resources you use are online, such as cloud-based SaaS, ERPs, or CRMs. Integrate.io explains why data integration is such a big part of data management for Ecommerce and the benefits of an intuitive ETL and ELT tool.

This is a guest post with exclusive content by Bill Inmon. Bill Inmon “is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, first magazine column, held the first conference, and was the first to offer classes in data warehousing.” -Wikipedia. Our key points: One of the characteristics of most computing and analytical environments is that the environment consists of only one type of data.

While advancing technology is beginning to bring us electric vehicles, most vehicles on the road still operate on fossil fuels. This includes the commercial vehicles used in major fleet operations. Traditionally, gathering metrics regarding a driver's driving style, vehicle speed, cruise control usage, diagnostics, drive cycle, a vehicle's engine, and other factors has been quite difficult.

This is a guest post with exclusive content by Bill Inmon. Bill Inmon “is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, first magazine column, held the first conference, and was the first to offer classes in data warehousing.” — Wikipedia. Our critical points: Data warehouses are the whack-a-mole of technology.

Customer service has always been the underdog that significantly affects a business’s performance but is always overlooked due to a lack of time and resources. While businesses focused on generating more revenue, they missed an important contributor to that revenue- a positive customer experience. Using the customer’s perspective to stay aligned with the evolving customer needs is essential for your business to foster a customer-centric culture.

Ecommerce companies like yours collect and store data for analytical activities such as business intelligence (BI). However, many organizations don't know how to harness the power of data or improve the efficiency of analytics. Data observability solves the problems of the modern data infrastructure by helping you understand the current state or health of data in your Ecommerce enterprise. You can detect and diagnose issues that might occur during data integration and improve data quality for analysis.