Data careers are becoming increasingly important and popular all across the globe, simply because “data” is the new currency of the data economy. The pandemic gave the needed push to accelerate the digital transformation of global businesses, and currently, the primary market differentiator is an enterprise’s data infrastructure readiness. This data infrastructure comprises systems, processes, […]
Data Warehouse vs. Data Lake Technology: Different Approaches to Managing Data
Solving business problems using big data depends upon the approach taken. For example, if an organization only knows data warehouses, then challenges will be framed to fit using a data warehouse. As Abraham Maslow, a prominent psychologist eloquently said “I suppose it is tempting, if the only tool you have is a hammer, to treat […]
Big Data Ecosystem Updates: Hadoop, Containers, and VMs Explained
Twenty years ago, a startup called VMware brought in business by providing a platform to create nonphysical machine virtualizations, such as Linux, Windows, and others. As server processing capacity increased, basic applications couldn’t maximize the use of all the abundant new resources. Enter Virtual Machines (VMs), designed to run software on top of a physical […]
Knowledge Graphs for Robust Data Governance
More data, more sources, more conflicts. More self-service reporting, more cross-functional analytics, more government and industry regulations. Without a way to govern all the data in their possession, businesses are not going to do well at creating reports or dashboards or building data consensus across departments. Nor will they feel confident that they’re not missing […]
A Brief History of Database Management
A database management system (DBMS) allows a person to organize, store, and retrieve data from a computer. It is a way of communicating with a computer’s “stored memory.” In the very early years of computers, “punch cards” were used for input, output, and data storage. Punch cards offered a fast way to enter data and […]
A Brief History of Data Silos
The original purpose of a data silo was to keep secrets. People have been keeping secrets for a long, long time. Prior to the written word, keeping a secret meant not sharing specific information with anyone else, verbally. And then came the written word. Secrets could be shared accidentally, or even stolen. Life became more […]
The Data Warehouse, the Data Lake, and the Future of Analytics
Data lakes were created in response to the need for Big Data analytics that has been largely unmet by data warehousing. The pendulum swing toward data lake technology provides some remarkable new capabilities, but can be problematic if the swing goes too far in the other direction. Far from being at the end of this […]
NoSQL Databases: The Versatile Solution for Continuous Intelligence
Most businesses tend to rely on relational database management systems (RDBMS) to provide business insight, including continuous intelligence. Cloud relational databases have improved computing power they bring to the table, to handle more massive amounts of data. However, relational databases, even ones in the cloud, face two issues. They have a harder time with the […]
Graph Database vs. Document Database: Different Levels of Abstraction
“Remember that every science is based upon an abstraction. An abstraction is taking a point of view or looking at things under a certain aspect or from a particular angle. All sciences are differentiated by their abstraction.” (Fulton Sheen) Graph and document databases (aka document stores), also demonstrate this principle. A few years, graph databases […]
So You Want to be a Big Data Analyst?
With the increasing use of big data by organizations in every field, the need for big data analysts will continue to grow. Big data analysts examine vast amounts of varied data. They uncover hidden patterns, customer preferences, and market trends. One of the primary differences between a big data analyst and a data scientist is […]