Data observability is the term given to a system of practices and processes, designed to fully understand the health and functionality of a company’s data as it is created, collected, processed, and generally flows through the business. […]
Read More… from 4 Pillars of data observability, and why are they important?
With more than 36,211 companies utilising data warehousing in 64 technologies, and covering industries across the globe, it is unsurprising that data-driven and tech-savvy companies are looking to find the best technology partners for their business needs and are making more and more use of the space and options made available. […]
Read More… from Databricks vs Snowflake: Whats right for you?
Technology continues to evolve at a rapid pace, and companies are finding that if they do not get ahead of the need to update and upgrade, they are losing valuable data and opportunities, which their competitors are picking up instead. […]
Read More… from Comparing Grafana and Datadog: What’s the top choice for 2023?
According to the McKinsey Global Institute, data-driven organisations are 23 times more likely to acquire customers. A business’s data used effectively can be incredibly useful for a business to understand performance, make data-driven decisions and remain agile. World-renowned brands such as Netflix and Starbucks have adopted a data-first approach to drive significant growth and success. […]
Read More… from Data engineering best practices you need to implement
Businesses produce a lot of data, and handling that effectively can mean the difference between an effective operation or loss of opportunities; 90% of large enterprises have now adopted a multi-cloud infrastructure, and 60% of global corporate data is now stored on the cloud. […]
Read More… from Enterprise cloud modernisation VS Enterprise cloud migration – what’s best for you?
There are a lot of different data warehousing solutions on the market, and once you have made the decision to undertake data migration from one provider to another, it is absolutely vital that you not only choose the right technology partner but that you also plan your data warehousing solutions to meet your current needs […]
Read More… from 4 Essential steps to data warehouse migration
When it comes to effective database management and data engineering tasks, NoSQL services are a non-tabular option that are often well suited for big data, real-time web apps, online shopping, social networks, and Internet of Thing (IoT) tasks, amongst others. […]
Read More… from MongoDB Vs DynamoDB – What NoSQL technology is best for you?
In order to manage your data effectively and securely, you need to have the right tools for the task. When it comes to database management systems, Structured Query Language (SQL) is used for processing information that is laid out in a relational database (where the information is stored in tabular form, with rows and columns […]
Read More… from MSSQL vs MySQL – How to make the best choice for your business
Bad data can be responsible for the loss of around $15 million per year according to a study by Gartner. Poor quality data can cost your organisation in more than one way including data storage, loss of productivity and more. Implementing processes for data pipeline monitoring will ensure your data pipelines are running in line […]
Read More… from Data pipeline monitoring strategies, technologies and metrics to measure
Migrating to the cloud can be highly beneficial for your business, it allows you to be more flexible, work with agile operations, innovate at a faster pace, and can reduce costs – especially when you have been spending on server hardware and storage space. […]
Read More… from Migrating to the cloud – Lift-And-Shift VS Modernisation
