I recently started a new blog series on why Real-Time Decision-Making is required during periods of market uncertainty. In this next blog, lets level set on exactly what is Real-Time Decision-Making and why it matters so much more during periods of market uncertainty and business disruption. Naturally, what got me thinking about all of…
Hybrid clouds seem to be the way the wind is blowing. According to the Enterprise Strategy Group, the number of organizations committed to or interested in a hybrid cloud strategy has increased from 81% in 2017 to 93% in 2020. But what exactly is a hybrid cloud? Turns out, there are a lot of…
Database Historians...History? Why a modern time-series capable database can simplify yet enhance time-series data analysis. Despite the professorial image the term suggests, a data historian is not an instructor or researcher, but a purpose-build software solution. And evolutions in how operational data is used and managed have eclipsed the need for data historian software…
In the opening installment of this blog series—Data Lakes, Data Warehouses and Data Hubs: Do we need another choice? I explore why simply migrating these on-prem data integration, management, and analytics platforms to the Cloud does not fully address modern data analytics needs. In comparing these three platforms, it becomes clear that all of…
And why is it better than a Data Lake or an Analytics Hub? In the opening installment of this blog series—Data Lakes, Data Warehouses and Data Hubs: Do we need another choice? I explore why simply migrating these on-prem data integration, management, and analytics platforms to the Cloud does not fully address modern data…
Processing data in real-time Every organization processes data in many ways. For example, batch data process still exists for heavy data-process workloads, such as payroll. Many of these data processing requirements are executed by batch scheduling software; however, there is a growing need for data processing to be more automated and processed in real-time.…
Data Lakes, Data Warehouses, and Data Hubs - Do we need another choice? There’s a long-standing debate, dating back to the early days of Hadoop, about what kind of data repository is best for a given data analytics use case. A Data Lake? A Data Hub? A Data Warehouse? Despite Hadoop’s fall from grace,…
What is a modern data platform? When we ask this question, we get two different groups of answers. The first group is around the technology needed for data processing in today's business environment. In this group, the answers mention things like cloud services, containers, and on-prem. The second set of answers involves sources of…
This may seem like an academic question, but it is increasingly becoming a reality for modern businesses. What do you do when you have millions of records with infinite width and depth, and your data warehouse chokes? Do you trim your data? Do you add more infrastructure capacity? Or do you need to look…
When companies project data warehouse growth, they often look at a curve that mimic’s the growth of data in source systems. This approach works if all you are concerned with is storage growth. What is commonly overlooked is the compute growth curve for processing updates to your data. As IT systems become more interconnected,…
Have you ever tried to join your fact and dimension tables together to generate operational analytics? If you want to perform large scale data analysis on things like customer churn, you’re probably going to need to do this. The problem is, these tables are very large, and when you bring them together, the resulting…
Artificial Intelligence (AI) is the core of the next wave of IT systems, and it is time to get ready. The past year has seen tremendous growth in the adoption of artificial intelligence systems to help companies improve operational insights and provide enhanced customer service experiences. If you aren’t leveraging AI to support your…
Part Two: Rethinking What Client-Server Means for Edge Data Management Over the past few weeks our SQLite Blog series has considered the performance deficiencies of SQLite when handling local persistent data and looked at the performance complications created by the need for ETL when sharing SQLite data with back-end databases. In our last installment—Mobile…
Part One: Mobile may be IoT—but, when it comes to data, IoT is not Mobile Three weeks ago, we looked at the raw performance—or the lack thereof—of SQLite. After that, we looked at SQLite within the broader context of Modern Edge Data Management and discovered that its performance shortcomings were in fact compounded by…
How well do you know your customers? Do you know what they buy? Do you know when and why they make purchases? Do you know who influences their buying behavior? Do you know how price sensitive they are and what types of promotions they respond to? You should know these things. Connected data can…
The Opening of the Box As was the case with Pandora's box, once the lid is opened on cloud technology and you realize that perhaps the shiny new object interior didn't provide what you expected from your investment in the technology, it may be too late to change directions. So is the case with…
