Category

Data Warehouse

Category

While we say data lake vs. data warehouse, these two technologies are actually quite complimentary. Read on to see why. Data lakes and data warehouses are critical technologies for business analysis, but the differences between the two can be confusing. How are they different? Is one more stable than the other? Which one is going to help your business the most? This article seeks to demystify these two systems for handling your data. What Is…

In this second post out of a four post series, discover how to build a data warehouse by reading the 5 steps listed below. Over this series of four posts, I explore the keys to a successful data warehouse. Last time, I started with design—a reasonable place to begin! The topic of this post is, build, with operation and maintenance to follow. Even with a beautiful design model in your mind’s eye, the question of how…

With each passing day, we accrue more data than ever. In the digital era, data warehouses are shaping up to be business-critical processes. Do you struggle with data warehouses? Are you baffled by the benefits they offer? Can you tell the difference between a “database” and a “data warehouse?” While the scope and scale of data warehouses may be a little overwhelming, at the end of the day they’re fairly simple to understand, and when used…

I have always been fond of two things: cooking and analytics. Believe it or not, there are many correlations between cooking your perfect recipe and getting that perfect analytical dataset that drives actions. Yes, we know that when in doubt, follow your heart, or so they say. And when it comes to your enterprise, the parallel should be that whether in doubt or not, always follow the data. Data is the driving force, the fuel…

Data warehouses have been around for several decades, serving as a central repository of integrated data from disparate sources that meet an enterprise’s reporting and data analysis needs. With the recent advent of newer analytical capabilities driven by machine learning algorithms and a wide array of computational paradigms and data formats, the data warehouse is undergoing a rather rapid modernization into an analytics platform and ecosystem. While there are several aspects that make up what can be…

Snowflake Computing delivers a modern, cloud-based data warehousing platform which is giving traditional database vendors a run for their money. Built from the ground up to exploit the capabilities of dynamic cloud infrastructure, Snowflake is available as an entirely managed data warehouse on AWS and Azure. Snowflake and Databricks IntegrationSOURCE: SNOWFLAKE Databricks is a Big Data company that offers a commercial version of Apache Spark on mainstream public cloud platforms including AWS and Azure. Its…

The global data lake market was valued at $7.6 billion in 2019 and is expected to grow more than 20.6% from 2020 to 2027. These powerful, cloud-based platforms offer a holistic view of marketing initiatives. They also aid exploration and research by utilizing advanced analytics, artificial intelligence (AI) and machine learning to comb through large amounts of information. But before brands, agencies, and publishers dive in, they need to understand the risks and rewards data lakes inherently bring. …

There are two words that that data industry loves to use today: complexity and simplification. The latter is obviously intended to counter the former… and the ultimate objective is the Holy Grail of Data Nirvana (HGDN) i.e. a so-called ‘single source’ of data where firms can look at every aspect of their business on one software platform. This is the rationale that SAP is currently keeping at front of mind as it develops what it…

Over 25 years ago, the average business was just becoming acquainted with how to effectively capture and store its data. Back then, data was used to help retail companies manage their inventories, enable commercial airlines to effectively maintain their flight schedules, and allow service-oriented businesses to capture and store their customer contact information. The pace was slower, and the information systems used to compute silo data queries were capable of delivering on time and on-premise.…

Over this series of four posts, I explore the keys to a successful data warehouse. Last time, I started with design—a reasonable place to begin! The topic of this post is, build, with operation and maintenance to follow. Even with a beautiful design model in your mind’s eye, the question of how to build the data warehouse raises its ugly head! Ugly, because no matter how lovely the model, implementation is always hobbled by the less…