Tag Archives: data quality
AI-Ready Data Explained with Examples
AI-ready data usually refers to data that has been prepared in such a way that it can be effectively used for training artificial intelligence (AI) and generative AI models. In this blog, we will learn about what are the most common attributes of AI-ready data. The following are the top most 5 attributes that AI-ready data would need to have. Data must be: Check out this Gartner paper for further details – We Shape AI, AI shapes us.
Mastering Data Quality KPI Dashboards: Concepts, Examples
In the digital age, where data is often likened to the new oil, ensuring its quality is not just an operational necessity but a strategic imperative. In every organization, from small startups to global enterprises, the ability to trust and accurately interpret data can be the difference between insightful business decisions and costly missteps. This is where data quality Key Performance Indicators (KPIs) and their visualization through dashboards become pivotal. In this blog, we aim to navigate you through the multifaceted world of data quality, focusing on understanding, designing, and implementing effective KPI dashboards. Whether you’re a data analyst, a business intelligence professional, or just someone passionate about data-driven decision-making, …
Data Quality Characteristics & Examples
It is no secret that data is an essential component in the day-to-day operations of businesses—as well as the decision making processes. To ensure trust and reliability on the data, organizations must pay close attention to the quality of their data. In this blog post, we will discuss some of the key characteristics that make up quality data, diving into each characteristic and providing examples along the way. Good data governance strategies are also essential for maintaining high quality datasets across an organization’s entire IT infrastructure. These strategies include quality control processes for entering new data into the system; establishing internal documents with procedures for validating all incoming information; assigning …
Data Readiness Levels Assessment: Concepts
Data readiness levels (DRLs) and related assessments are an important part of data analytics. Data readiness levels is a concept where different stages represent the quality and maturity of data. Data science is becoming increasingly popular, but not all companies have the right level of data readiness for this type of work. Performing data readiness levels assessment is important because it gives an insight into the quality and quantity of your current datasets and helps determine future success of the data analytics project. This blog post will explain what data readiness levels are and why assessment tests are important in relation to them. What are data readiness levels? Data readiness …
I found it very helpful. However the differences are not too understandable for me