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Turning Data into Value with Azure Synapse Analytics and Power BI
Businesses are under pressure more than ever to cut costs, generate increased revenue and improve customer satisfaction. Business initiatives, and their performance and success, will measure business leaders during the time of the pandemic and there is pressure on leaders to invest their organisation’s efforts towards initiatives that demonstrate success while tackling these issues.
The COVID epidemic has encouraged leaders to take the opportunity to show flagship successes by spearheading data projects to produce value for the organisation. Value can mean different things to different organisations, such as sales turnover, customer satisfaction or reduced costs. Azure Synapse Analytics can help with deriving business value in a profusion of ways.
Easy Analytics And Data Visualisation Part 1 — Data Engineering With Power Query
In this blog series, we will examine common scenarios in Business Intelligence using Finance Data. The series will explore common use cases that often occur in business intelligence, such as pivoting data, changing the format, and working with dates. The blog series will use Power BI and Azure Synapse Analytics to showcase the data quickly and scale effortlessly to meet the business need.
The series is accessible to business users who may not be comfortable in coding, but who are familiar with Excel since all coding is supplied. Power BI is a good step for Excel users, and this blog series will cover some of the most common scenarios that an Excel user might come across during analytical work. The blog series does cover SQL and all code is provided.
There are a number of steps throughout the series, presented here at a high level.
You can watch the whole thing in this video, or click the button to continue reading the blog.
Easy Analytics And Data Visualisation Part 2 — Working With Sql In Azure Synapse Analytics
In this blog series, we examine common scenarios in Business Intelligence using Finance Data. The series explores common use cases that often occur in business intelligence, such as pivoting data, changing the format, and working with dates. The blog series uses Power BI and Azure Synapse Analytics to showcase the data quickly and scale effortlessly to meet the business need.
You can watch the whole thing in this video, or click the button to continue to part two of the blog.
Easy Analytics And Data Visualisation Part 3 – Visualising Azure Synapse Analytics Data In Power Bi
In this blog series, we examine common scenarios in Business Intelligence using Finance Data. The series explores common use cases which often occur in business intelligence, such as pivoting data, changing the format, and working with dates. The blog series uses Power BI and Azure Synapse Analytics to showcase the data quickly and scale effortlessly to meet the business need.
In the first post, we covered some simple data engineering with Power Query, and we imported the data into Azure Synapse Analytics storage. In the second post, we focussed on conducting tasks in Azure Synapse Analytics such as creating tables and views, testing the tables and formatting the data.
You can watch the whole thing in this video, or click the button for part three of the blog.
Moving From Business Intelligence To Predictive Analytics
In the last two years alone, 90% of the world’s data has been created (Source: IORG, 2019). Business leaders understand that their data is valuable, but many businesses collect data and static business intelligence reports but struggle to find a path from business intelligence reporting to analytics.
The purpose of Business Intelligence is to optimize the business, not simply create reports. When allocating budgets, it can be hard to prove a return on investment in Business Intelligence projects since the output is a series of reports or dashboards rather than a demonstration of business optimization.
Databricks And The Microsoft Modern Data Warehouse Enable Data Scientists
The big data analytics market is set to reach $103 billion by 2023 (Techjury, 2021). It is well documented that the volumes of data are increasing. However, what’s less clear is that as both data grows, so does the number of transformations and computations required to conduct all parts of the data journey inside an organisation.
Therefore, enterprises need a scalable compute platform for all parts of the data journey to include data that has a vague structure as well as more structured data sources. The journey includes data storage, but it also includes compute for other parts of the data journey in the organisation that are harder to see.
Top Ten Features Of The Microsoft Intelligent Data Platform
To help your organization move forward quickly with its innovation strategy, we have put together the top ten innovation-focused features of the Microsoft Intelligent Data Platform to support a data-driven strategy.
Organizations all over the world are keen to strive for innovation with their data, and boardrooms all over the world are keen to become data-driven. However, when the executive leadership team issues directions to their technology teams, it can seem very complicated to get started. For example, in a world that is full of technology, it can be challenging to identify software features that will help to drive innovation or help derive value from data. What should a company look for in features? What’s important and what isn’t?
The Microsoft Intelligent Data Platform For Executives
What do business leadership teams require from the Microsoft Intelligent Data Platform? What’s different from previous implementations of the Microsoft Data Platform, and how can it help businesses? There are plenty of articles that focus on technology, but in this post, let’s take a look at innovations from the perspective of the C-suite.
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