Your time and resources are precious, and when you are running a process that involves a lot of data, and potentially is costing you for every action (or inaction) – making the most of your budget is crucial. […]
Read More… from Data pipeline automation – what you need to know
Managing your data efficiently means understanding exactly what you are doing, the size of the data involved, and what pipeline structure is going to best suit your needs. Developing your data pipelines is a critical part of your strategic data development and business growth. […]
A data engineering team depending on the industry, size and type of business as well as scale type and form of data will differ in their structure, functions and day-to-day work. It is undeniable the invaluable benefits a good data engineering team can provide for a business whether you have a team in-house or work […]
Read More… from Building a data engineering team the right way
A managed service is the process of outsourcing specific functions this can range from software development to data management. Outsourcing these functions if you do not already have existing time and resources in-house can provide invaluable benefits can give you access to experienced and highly skilled professionals in the field. Managed data engineering teams, depending […]
Read More… from Managed data engineering teams – getting started
The bigger your company grows, the more data it will generate, and the more complex your data requirements become. There are a number of key challenges with data management, and if you are not prepared to make informed, researched decisions, you may end up spending time, money, and resources on data storage and management methods […]
Read More… from Batch, Stream, Real-Time Processing: A Comparison
One of the hardest parts of real-time machine learning is building real-time data pipelines, they need to be able to handle millions of events at scale in real-time, and be able to collect, analyse, and store large amounts of data. This means that the capacity for applications, analytics, and reporting all has to be robust, […]
Read More… from Key challenges with real-time data processing for your data pipeline projects
A data pipeline is a set of processes and associated tools that make the movement of data between a source and its target, automated. There are three key elements involved – a source, processing steps, and the destination. The processing steps you choose will depend on your needs, your software, and how your pipeline has […]
Read More… from How to approach stream processing for your data pipelines
Making the decision to move your data to the cloud is an important one, and it needs to be carefully considered before you start. The three essential stages of cloud migration cover: analysis of both your business needs and technical operation, risk analysis and a plan for the scope of the migration process and the […]
Read More… from Migrating your data to the cloud – what you need to know
Batch processing is a method for taking high-volume repetitive jobs and automating them into a series of steps which cover extraction, aggregating, organising, converting, mapping, and storing data. The process requires minimal human interaction and makes the tasks more efficient to complete, as well as putting less stress on internal systems. […]
Read More… from How to approach batch processing for your data pipelines
There are not many organisations around the world that are untouched by technology and that are not creating a huge amount of data through their day-to-day operations. How you sort that information, and whether it reaches its full potential in usability, functionality, and cost-effectiveness will depend on how you handle it, and whether you have […]
Read More… from Data Warehousing technologies – making the right choice
