Graph databases play a key role in fraud detection within intricate, complex networks, helping security teams keep pace with modern fraud techniques that are becoming increasingly more sophisticated. Graph databases can identify patterns and relationships in big data, reducing the level of complexity so that detection algorithms can effectively discover fraud attempts within a network. […]
7 Essential Roles for a Successful AWS Migration
Increasingly more organizations initiate AWS migration due to the advantages provided by the AWS cloud platform. According to The Business Value of Migrating to AWS survey, 43% of AWS adopters report lower time-to-market for new features, 20% report infrastructure cost savings, and 66% note an increase in administrator productivity. However, AWS migration is a challenging task requiring a […]
Architecting Real-Time Analytics for Speed and Scale
In today’s fast-paced world, the concept of patience as a virtue seems to be fading away, as people no longer want to wait for anything. If Netflix takes too long to load or the nearest Lyft is too far, users are quick to switch to alternative options. The demand for instant results is not limited […]
OLTP Database Solutions for Today’s Transactions
Online transaction processing (OLTP) enables rapid, accurate data processing for most of today’s business transactions, such as through ATMs, online banking, e-commerce, and other types of daily services. With OLTP, the common, defining characteristic of any transaction is its atomicity, or indivisibility. A transaction either succeeds as a whole, fails, or is canceled. It cannot […]
Modeling Modern Knowledge Graphs
In the buzzing world of data architectures, one term seems to unite some previously contending buzzy paradigms. That term is “knowledge graphs.” In this post, we will dive into the scope of knowledge graphs, which is maturing as we speak. First, let us look back. “Knowledge graph” is not a new term; see for yourself […]
Spark vs. Flink: Key Differences and How to Choose
Apache Spark is an open-source, distributed computing system that provides a fast and scalable framework for big data processing and analytics. The Spark architecture is designed to handle data processing tasks across large clusters of computers, offering fault tolerance, parallel processing, and in-memory data storage capabilities. Spark supports various programming languages, such as Python (via […]
Semantic Technology and Integration 101: What It Is and Why It Matters
New technologies like ChatGPT are all the rage, as they aim to answer questions and provide information that makes our lives easier. Yet, the validity of the results generated has come under scrutiny and, as a result, much emphasis has been made on how organizations can get relevant and trustworthy data into the hands of […]
Best Practices in Data Pipeline Test Automation
Data integration processes benefit from automated testing just like any other software. Yet finding a data pipeline project with a suitable set of automated tests is rare. Even when a project has many tests, they are often unstructured, do not communicate their purpose, and are hard to run. A characteristic of data pipeline development is the frequent […]
How to Work with Unstructured Data in Python
All our online actions generate data. Even if we don’t write posts, comment, or upload other content, we leave our traces by being silent observers. This leads to predictable results – according to Statista, the amount of data generated globally is expected to surpass 180 zettabytes in 2025. On the one hand, having many resources to make […]
What to Expect in 2023: AI and Graph Technology
2023 will bring exciting advances in AI and graph technology. One of the most compelling innovations will be the ability for quantum programs to be turned into graphs and vice versa. Natural language understanding will become part of AI models. The adoption of standards-based semantic layers will spike as they enable data selection through business terms. Graph […]