The term “digital transformation” (DT) encompasses the holistic framework and the associated strategy designed for integrating technology, business processes, and employee effort to get the maximum value for business customers. In a digitized business model, the “customer journey” is the central focus. While creating the DT framework, the business operators develop business models that are […]
Data Science vs. Data Analytics
The data scientist and the data analyst represented two of the “most in-demand, high-paying jobs in 2021.” The previous year, the World Economic Forum Future of Jobs Report 2020 listed these jobs at the top of a list representing most in-demand jobs across industries. In data analytics, which is often referred to as business analytics, […]
How Does Data Management Drive Efficiency for Organizations?
Data-driven analytics continue to deliver sophisticated solutions for manufacturing efficiency, early disease detection, and smart capabilities building in workplaces. Thus, industry operators and leaders continue raise their expectations and demands from data technologies with every passing year. Brent Gleeson of Forbes, who regularly contributes about organizational excellence, warns that in spite of having the best […]
Maturing Business Intelligence with Data Governance
Data Governance (DG) ensures that enterprise data, the most valuable business asset, is preserved and used in the most efficient and safest manner. That said, Data Governance puts immense demands on organizational policies, processes, technologies, and lastly on accountable staff to develop an executable framework, from its core architecture to implementation stages. Enterprise Data Governance […]
Data Management Technology: Trends & Challenges
The last two years have been significant in the growth of Data Management technology, mainly because of the pandemic and associated factors. Almost overnight, large, medium, and small organizations located far and wide, suddenly realized the importance of online business models and hosted Data Management services. The coronavirus gave the final push to global enterprises […]
Data Science Best Practices
When done right, Data Science delivers a lot of measurable values like improved products and services, enhanced customer experiences, sales growth, new business developments channels, and overall business efficiency. However, according to most reliable industry publications, most Data Science projects fail because the Data Science best practices are not followed. Why Do Businesses Need Data […]
The Mainstreaming of Multi-Cloud: Good or Bad?
The business world is increasingly reaching out to the public cloud for stable data center operations at optimized cost but at scale. In the recent years, managed services and multi-cloud consultancy firms have cropped up to reduce the chances of multi-cloud implementation failures, but the general lack of deep understanding and skilled employees are still […]
Data Science vs. Decision Science: A New Era Dawns
Data Science vs. Decision Science: Basic Descriptions In Data Science, a variety of advanced technologies like data mining, statistics, predictive analytics, AI, and machine learning are used in conjunction to deliver solutions for business problems. In Decision Science, analyzed data is “interpreted” to arrive at business decisions that meet specific objectives. So while Data Science […]
The Intersection of Self-Service Analytics and Machine Learning
The terms “self-service analytics” (SSA) and “machine learning” (ML) are frequently used interchangeably, but the concepts behind these terms are a world apart. In self-service analytics, specific tools are designed to aid the user in inputting data or interpreting results (output). On the other hand, a machine learning algorithm is a special software that has […]
Data Management vs. Data Science
The shift in the business perception of data has now catapulted Data Management into new heights. Data Science is a core component of Data Management now, but Data Management and Data Science are often seen as two different activities. Working among data analysts, data engineers, and DBAs, data scientists spend their time getting the data […]