Machine learning (ML), is a subdomain of Artificial Intelligence and is about teaching machines how to learn from a set of data. When applied properly, the machines learn to characterise patterns automatically in order to make strategic decisions. Not only is it a science, but it is also an art.
On-premise data warehouses are large, costly, inflexible and require constant upkeep, that’s why most businesses are moving to data clouds. We’ve been helping our clients transition for years and we anticipate these projects increasing tenfold as the industry accepts clouds for what they are – easy, secure, scalable and cost-effective.
In this blog post, we will explore why data wrangling is so important in today’s data-driven landscape and how the Designer Cloud can help simplify and accelerate this process. Keep reading to learn how you can free up much needed resources for more crucial activities.
On-premise data warehouses are large, costly, inflexible and require constant upkeep, that’s why most businesses are moving to data clouds. We’ve been helping our clients transition for years and we anticipate these projects increasing tenfold as the industry accepts clouds for what they are – easy, secure, scalable and cost-effective.
Data can only be used to generate accurate insights when it’s properly formatted and cleaned thoroughly. Therefore, the data cleansing and preparation process is a very crucial step to ensure good data hygiene as well as accuracy.
I’m pretty sure we’re all familiar with the phrase ’Data is the new oil’. The phrase owes all credit to Clive Humby, a British Mathematician who proclaimed and gathered interest in it until The Economist published an edition titled “The world’s most valuable resource.”
Prescriptive Analytics is one of the most valuable and complex form of analytics. It inherits the output of other forms of analytics to transform and produce applicable insights and solutions.
In this blog, we will be looking at data lakes, including how they differ from data warehouses and how data is ingested, before concluding with a sample hybrid cloud data lake / warehouse implementation.
In this blog, we will explore data modelling and ingestion concepts that can enable organisations to harness the power of big data.
The industry has been steadily moving toward to the cloud to ease these burdens however, the benefits don’t stop there. Moving to the cloud allows users to easily access data through a browser, democratising analytics and providing the ability to scale.
In this webinar you’ll learn about:
👍 Improving existing processes with Alteryx
👍 Data Formatting & Text Parsing use-case
👍 Reconciliation use-case
👍 Commonly used tools
👍 Inputs & outputs, macros, apps (and more!)
