User stories are development tasks often expressed as follows: persona + need + purpose A key component of agile software development is putting people first.
The Microsoft Power BI team have released a preview Data Lineage feature and I couldn’t be happier! The Power BI lineage view displays the lineage relationships between all the artifacts in a workspace, and all its external dependencies.
Businesses need a clear line of sight on data asset ownership and stewardship. This has traditionally been in the hands of the IT department, but unfortunately the projects can become deprioritized as IT fight other battles elsewhere. IT can do so much, but the business do need to bring things to the table. Hence, we now see accessible tools appearing in technology such as Power BI.
I’m pleased to announce that the University of Washington are running a Foundations of Data Analysis course, starting in January 2020. In this 10-week course, you’ll learn how to understand and analyze data. We’ll start with fundamental data-related concepts, terminology and ethical considerations. You’ll learn how to articulate business problems and identify required data. Using Microsoft Excel and SQL, you’ll practice gathering, cleaning and organizing data. Finally you’ll use Tableau to effectively describe, analyze and visualize data.
From the business intelligence perspective, it is incredibly useful to compare AWS RDS and Microsoft Azure SQL Database. As a freelance industry analyst who has worked with GigaOm, I’m pleased to see the GigaOM Transactional Field Test derived from the industry-standard TPC Benchmark™ E (TPC-E) report which compares Amazon Web Services Relational Database Service (AWS RDS) and Microsoft Azure SQL Database.
I’m excited to be attending ASG Technology’s Evolve19 event in Dallas, Texas on October 21 – 23. I’m particularly interested in learning more about metadata
Data debt is like technical debt, only visible in bad data, poor data quality, and an underuse of data-oriented technology to help make better decisions. It is the overhang of projects, whether they went well or poorly.
Technical debt is the implied cost of additional rework caused by choosing an easy (limited) solution now instead of using a better approach that would take longer. It also applies to data debt; the cost of ignoring the data by choosing the quick or easy solution earlier at a previous point, which now takes longer to resolve.
At some point, however, we need to pay back data debt if we are to succeed in making better decisions.
Credit to stux-12364 for the jigsaw image. When you install SSDT, you can find that the SSIS Toolbox components are all missing. I am writing
Customers want their data good, fast, cheap and easy. A tall order, right? One of the biggest challenges that I see with data warehousing in
I’m excited about Power BI dataflows, since I believe it’s a great way forward for companies to sort out the issue that nobody likes to
I am writing some SQL to form the basis of views to pull data from a Microsoft SQL Server source into Azure SQL Database, and
how to find the tenant in Power BI.
Azure SQL Database is introducing two new features to cost-effectively migrate workloads to the cloud. SQL Database Hyperscale for single databases, available in preview, is a