Data quality refers to the planning and implementation of quality management measures for the data that companies generate. The idea is that the data should fit the end goal of the data consumer’s needs – and must follow specific quality dimensions to be deemed fit for use. The role of a data quality analyst (DQA) is to ensure […]
Machine Learning Solutions
Machine learning solutions can be considered a subdivision of artificial intelligence, with multiple machine learning algorithms combined to create artificial intelligence. Some of these algorithms can, however, be used to accomplish specific, limited tasks, ranging from answering phones to recognizing images. Machine learning (ML) solutions are normally used in situations requiring adaptability, a limited variety of […]
What Makes Data Intelligence Intelligent?
Every day, trillions of data points are generated, and, in theory, organizations can harness this data to make better, more informed decisions. But it’s precisely the vast scale of available data that makes it so hard to manage. According to IDC, data professionals spend 80% of their time searching for and preparing data and only 20% […]
The Importance of a Data Governance Roadmap
A Data Governance (DG) roadmap provides a detailed plan or strategy, normally with a list of tasks that must be accomplished for improving or “maturing” a DG program. It should also list the people who are responsible for completing specific tasks. A Data Governance roadmap often includes incorporating Data Governance best practices and is typically based on […]
The Role of Decision Science in Shaping Business Analytics
The field of decision science focuses on making data-informed decisions. Decision science helps to analyze the impact of a decision on the business. The best decisions are often made with a combination of data and precise business questions. The more precise the questions, the more precise the data requirements will be. Harvard’s Center for Health […]
Data Modeling 101
Data Modeling creates a visual representation of a data system as a whole or as parts of it. The goal is to communicate the kinds of data being used and saved within the system. A data model should also show the data’s relationships, how the data can be organized, and the formats used. A data model can […]
Key Trends in Data and Analytics
In today’s world of unprecedented connectivity and advances in technology, the benefits of big data are accessible to even modestly scaled businesses. Indeed, business leaders who resist the shift to digital transformation do so at their own risk. But harnessing the power of data and analytics requires careful planning, preparation, and commitment. Where to begin? […]
Data Literacy Best Practices
The term “data literacy” refers to the ability to extract meaning from data. IDC, the global market intelligence expert, has predicted a “ten-fold increase in worldwide data” by 2025. It’s no wonder many data-driven organizations are in a race for an enterprise-wide data literacy initiative, with the vision of transforming their employees into data-literate workers. Global […]
Writing a Data Management Plan
A Data Management plan (DMP) is normally a one- or two-page summary, outlining how data will be handled during a research project, and after it has been completed. The goal of a Data Management plan is to consider the many aspects of Data Management (such as data preservation, metadata generation, and analysis) before the project begins. It […]
Data Analytics Tools: Features and Functions
Today’s business environment is inherently data-driven. Businesses need data to stay competitive and grow their market presence – data is regarded as the “currency” of the modern world and the key to the future. Data analytics, in turn, is the process of discovering trends and patterns in large amounts of data to make intelligent decisions. It […]