It offers many features in the data and analytics space, ranging from Platform-as-a-Service (PaaS) solutions for data and big data management and analytics, to multiple AI and machine learning offerings, to specialized Software-as-a-Service (SaaS) solutions such as Azure Purview,which is a unified data governance solution that helps users manage and govern their on-premises, multi-cloud, and SaaS data.
Development teams need specific insights into the microservices they are responsible for, reflecting particular metrics, dashboards, custom alerts, service-level objectives (SLOs), or even automatic remediation steps. But setting up these tools requires in-depth knowledge and causes massive effort if done manually.
With the rise of unstructured big data, which now comprises roughly 80% of all enterprise data under management, a new wave of data repositories has come into use that don’t always use a data warehouse.
Data lakes are different. Their purpose is to store, secure and avail access to aggregated combinations of structured and unstructured data that are tailored to a particular area of the business.
Core to the cloud total addressable market (TAM) analysis are driving factors such as workload adoption, workload spend, and workload expansion, which we discussed and validated with a number of practitioners and end users in the field.
We ran three scenarios and believe that the one we consider most likely will result in a $2 trillion public cloud market in the foreseeable future (a 10–20-year timeframe)
The Asia-Pacific region has long been a strong manufacturing base and the sector continues to be a strong adopter of the Internet of Things (IoT). But as the latest Microsoft IoT Signals report shows, IoT is now much more widely adopted across verticals, and across the globe, with smart spaces—a key focus for many markets in the Asia-Pacific region—becoming one of the leading application areas.
Whilst AI will spur the development of even more new creative business applications, it will also help humans to find more time for being creative in their daily work.
Two of the most talked-about topics in the world of software development right now are Kubernetes and infrastructure as code (IaC).
In other words, as companies adopt new modern infrastructures (e.g., Kubernetes), novel security challenges arise that are best addressed by modern processes (e.g., DevSecOps).
They gave me examples of some as simple as a chatbot and others as complex as end-to-end dedicated platforms. We won’t ultimately answer the question in this blog, but we can work towards that end
The vision of fully integrated IT and operations that deliver new insights, inform business decisions, and strategically manage performance was, for a long time, little more than an aspiration.
This article discusses some of the risks customers may unwittingly encounter when moving their database to a database as a service (DBaaS) in the cloud, especially when the DBaaS leverages open source database software such as Apache Cassandra, MariaDB, MySQL, Postgres, or Redis
The Forrester Wave™: Public Cloud Container Platforms, Q1 2022 scored eight cloud providers on 29 criteria ranging from cloud-native application development to control plane configuration and infrastructure operations to security.
Similarly, 92% agreed that “Due to drastic changes in customer behavior or other factors during the pandemic, reliable real-time data became even more important for business decisions.”
95% of respondents, for example, agreed that “Making decisions based on accurate, timely analytics and insights has become as important as having accurate transactional data in my organization.”
When appropriately crafted, data lakes can be a centralized source of truth, offering team members valuable flexibility to examine information that impacts business decisions.
A well-maintained data lake has the real potential to transform your business by offering a singular source for your company’s data—in whatever form it may be—that enables your business analysts and data science team to mine information in a scalable, sustainable way.
Reliable real-time data and analytics for decision-making became more critical. But many IT organizations couldn’t deliver; survey respondents said that the information and insights needed by the business often weren’t available.
There were high levels (95%) of agreement with the very rational statement that, “My organization makes decisions on where/how to process data for analytics and AI based upon the best platform attributes (latency, security, resiliency, and performance/ cost).
