Download the slides here>> About the Webinar Today’s enterprises have an unprecedented variety of data store choices to meet the needs of their varied workloads. Because there is no one size fits all when it comes to data stores, this can lead to confusion and chaos. Enterprises have many needs for databases, including cache, operational, data […]
Mind the Gap: Analytics Architecture Stuck in the 1990s
Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the data chasm. This month, we’ll look at analytics architecture. From day one, data warehouses and their offspring – data marts, operational […]
AAA Webinar: Demystifying AI for Business Leaders
Download the slides here>> About the Webinar In this webinar, we will clarify AI for business leaders and describe the key challenges and opportunities they face. We will discuss how to assess the feasibility and viability of AI and automation solutions, how to design and implement them in alignment with business goals and values, and […]
Securing Data in Transit for Analytics Operations
Most enterprises today store and process vast amounts of data from various sources within a centralized repository known as a data warehouse or data lake, where they can analyze it with advanced analytics tools to generate critical business insights. Modern data warehouse platforms such as Snowflake, AWS Redshift, Azure Synapse Analytics, and IBM Db2 are built with […]
Demystifying AI: What Is AI and What Is Not AI?
In recent months, particularly following the release of ChatGPT, there has been an unprecedented surge in interest surrounding artificial intelligence (AI). This heightened attention spans across a multitude of sectors, including business enterprises, technology companies, venture capital firms, universities, governments, media outlets, and more. As the interest in AI is intensifying, some companies have even […]
Beyond the Basics: Advanced Tips for Effective Data Extraction
Data extraction is a cornerstone in data analytics, enabling organizations to extract valuable insights from raw data. While basic extraction techniques are fundamental, understanding advanced strategies is crucial for maximizing efficiency and accuracy. This article will explore advanced tips for effective data extraction, shedding light on automation tools, leveraging APIs and web scraping techniques, enhancing […]
RWDG Webinar: How Generative AI and LLMs Shape Data Governance
Download the slides here>> About the Webinar Dive into the cutting-edge world of Data Governance by spending this hour focused on the impact generative AI and large language models (LLMs) are having, and will have, on Data Governance implementations. However, this addresses only one side of the relationship. In this webinar, Bob Seiner will explore […]
ADV Webinar: What The? Another Database Model — Vector Databases Explained
Download the slides here>> About the Webinar Vector databases are a type of database that use graph embeddings to represent and compare data, making them ideal for fuzzy match problems. Graph embeddings are created using machine learning algorithms and compress the attributes of data into a low-level representation. The process of creating a new embedding […]
Data Intelligence: The Key to Empowered People and Decisions
McKinsey analysts predict that enterprise employees will rely on data for almost every decision come 2025. If true, this development would mark a significant departure from the current business modus operandi. According to our research, only 25% of enterprise data professionals believe their organization’s decision-making process is data-backed or strategic. How are these two concepts – the perception of data […]
How to Become a Data Product Manager
Becoming a data product manager means taking responsibility for the development and management of data products. Broadly speaking, a data product is any software or algorithms that use data to accomplish a goal. The data product manager is a management position, and requires several years of experience within the data industry to be done well. […]