Machine learning makes improving Data Quality easier. Data Quality refers to the accuracy of the data: High-quality data is more accurate, while low-quality data is less accurate. Accurate data/information supports good decision-making. Inaccurate data/information results in bad decision-making. So, intelligent decision-making can be supported by supplying accurate information through the use of machine learning. Machine […]
Data Science vs. Machine Learning vs. AI
In the data economy, data is king. Today, any business – small, medium, or large – thrives on its data assets. The recent trend of offering data-driven insights as a service has opened up a profitable revenue channel for businesses. Cloud computing and hosted analytics have brought data-as-a-service to the desktops of ordinary business users, […]
Master Data Management Best Practices
Modern businesses can stay competitive by using the best practices for master data management (MDM). These best practices promote the use of clean, accurate data about suppliers, customers, and products. This, in turn, supports better analytics and business decisions. A master data management solution supports the development of master data, which can provide consistent, accurate data […]
Developing a Data Strategy Template
Organizations want a solid and usable Data Strategy template – a well-thought-out plan for a set of decisions that form a pattern, charting a high-level course of action – but face challenges. For example, only 30% of companies have impactful data strategies that align with some operations, resulting in wasted investments in improving analytics and business insights. Instead, most […]
How to Become a Business Intelligence Analyst
As with many buzzwords emerging from the intersection of business and technology, the phrase “business intelligence” (BI) is often misunderstood. In a nutshell, it refers to the skill and practice of extracting insights from data to realize new goals, strategies, trends, and values. A business intelligence analyst, working with a network of other knowledge workers (such […]
9 Key Data Management Principles and Practices
Business leaders often make corporate decisions in haste, based on data that is neither thoroughly analyzed nor understood. This can pose a serious threat to data-driven decision-making. Additionally, businesses risk losing a competitive edge by not following important business analytics practices. To get the full benefit of data-centric activities, businesses must follow several core Data […]
Are Data Scientists Needed in the Self-Service Analytics World?
As the world becomes increasingly data-driven, businesses are turning to self-service analytics to enable business users to perform their own data analysis tasks. In self-service analytics, business users can access and analyze data without assistance or support from IT personnel or data scientists. Direct access to ML-powered analytics platforms allows them to make better business […]
Data Lineage Use Cases
Data lineage can be described as a historical map of data’s journey within an organization. Use cases, in general, provide an example of how services or techniques can be used, and data lineage use cases are situations in which a form of data lineage can be used. Data lineage tools make tracking the data’s lineage […]
Understanding Data Mesh Principles
ThoughtWorks consultant Zhamak Dehghani defines data mesh as a “decentralized sociotechnical approach to sharing, accessing, and managing analytical data in complex and large-scale environments – within or across organizations.” This type of Data Architecture continues to generate interest among corporations, and data professionals will need to become familiar with data mesh architectures, such as those with data lakes or warehouses. […]
A Brief History of Data Modeling
Data Modeling is the “act” of creating a data model (physical, logical, conceptual, etc.) and includes defining and determining an organization’s data needs and goals. The act of Data Modeling defines not just data elements, but also the structures they form and the relationships between them. Developing a data model requires the data modelers to work […]