1: Build data-driven apps that learn and adapt
Applications show intelligence when they can spot trends, react to events, predict outcomes or recommend choices—often leading to richer customer experiences, improved business process, or addressing issues before they arise. The three key ingredients to creating an intelligent app are:
Ingest data in real time
Query across historical and real-time data
Analyze patterns and make predictions with machine learning
With Azure, you can make your applications intelligent by establishing feedback loops, and applying big data and machine learning techniques to classify, predict, or otherwise analyze explicit and implicit signals. Today, apps for consumers and enterprises can deliver greater customer or business benefit by learning from user behavior and other signals.
Pier 1 Imports launched a mobile-friendly pier1.com, making shopping online easier. It enabled the selection of delivery options like direct shipment, picking up products in the local store,…
When building applications with C# and SQL Server, it is often necessary to define codes in the database that correspond with enums in the application. However, it can be burdensome to maintain the enums manually, as codes are added, modified, and deleted in the database.
In this blog post, I’ll share a T4 template that I wrote which does this automatically. I looked online first, and did find a few different solutions for this, but none that worked for me as-is. So, I built this generic T4 template to do the job, and you can use it too.
Let’s say you’ve got a Color table and ErrorType table in the database, populated as follows:
Now you’d like enums in your C# application that correspond to these rows. The T4 template will generate them as follows:
Before showing the code that generates this, let’s point…
Upgrading your software can be daunting, Microsoft knows. The fast pace of business makes it easy to tell yourself, “I’ll do it later when I have time.” Microsoft gets it! But here are five key reasons to make time to upgrade to SQL Server 2016, which was named DBMS of the Year in 2016 by DBengines.com.
Seamless step-up without rewriting apps. Thanks to November’s SQL Server 2016 Service Pack 1 (SP1), SQL Server now has one programming surface across all editions. If you switch from Express to Standard, or Standard to Enterprise, you don’t have to rework code to take advantage of additional features. Time saved! In addition, the change brings access to innovative features across performance, security, and analytics not previously available in Express or Standard—a great reason to upgrade applications that run on those editions. The Enterprise edition of…
You’re using the new One Designer cross-versioning in SQL Server Integration Services, and everything breaks when you try to downgrade to SQL Server 2012. The little icon that indicates that everything has gone wrong shows up,
or when you try to interact with any custom components or tasks you get the following error, or something similar:
Now, there are three things worth checking:
Are your UpgradeMapping files set up correctly? They should point to a valid strong-named assembly, and use the same alias, for both versions of SQL Server that you’re attempting to deploy to. If not, fix this issue first and try again.
After migrating your custom objects, navigate to the UserComponentTypeName property (for PipelineComponents) or to the CreationName field of the corresponding DTS:Executable in the package XML.
These should contain either the alias (typically the qualified name of the class, i.e. Sample.SSIS.CustomTask),
or the strong-name associated with…
If you’ve ever been faced with the need to archive SQL Server data in order to save database space and/or improve query performance, you found that this would not be a simple task. Especially when the archived data must still be available to existing applications….
Previously. this could not be done without either database structure changes or application code changes or both. Potential solutions could involve partitioning the database table, which could help with performance, or changing the application queries to access different databases/tables in order to get current vs. archived data. Both potentially time consuming and intrusive remedies.
The Stretch Database functionality introduced in SQL Server 2016 uses Microsoft Cloud Services to make data archiving that is seamless to your applications possible. I have worked with Stretch DB in a lab environment and found that it has potential to solve…
In my previous post, I introduced the concept of temporal data, and explained at a high level how SQL Server 2016 implements temporal tables. This post dives into the details of exactly how you create and query temporal tables.
Let’s start with an ordinary table, and convert it into a temporal table. So I’ll create the Employee table, and load it up with some data.
To convert this into a temporal table, first I’ll add the two period columns and then I’ll enable temporal and set dbo.EmployeeHistory as the name of the history table.
Note that because we’re converting an existing table, this must be done in two separate ALTER TABLE statements. For a new temporal table, you can create it and enable it with a single CREATE TABLE statement. Also, and because this is an existing table with existing data, it’s necessary…
SQL Server 2016 introduces System Version Tables, which is the formal name for the long awaited temporal data feature. In this blog post (part 1) I’ll explain what temporal is all about, and my next post will walk you through detailed demos on temporal.
Temporal means, time-related, and in the case of SQL Server, this means that you get point-in-time access to a table, allowing you to query not only the table’s current data, but data as it appeared in the table at any past point in time. So data that you overwrite with one or more update statements, or data that you blow away with a delete statement, is never really lost. It’s always and immediately available simply by telling your otherwise ordinary query to travel back in time when looking at the table.
The mechanism behind this magic is actually…
Microsoft wants to make it easier for businesses to use their data. Otherwise, what’s the point? In SQL Server 2016 you’ll find a virtual tool chest full of features, all with one primary goal: unlocking your data and helping you create new ways of analyzing, visualizing and sharing it.
Building data-rich biz apps
The advent of machine learning and natural language processing made it easier to analyze unstructured data. The challenge was effectively integrating it with structured data, leading to more meaningful discoveries.
Enter SQL Server PolyBase, a feature in SQL Server 2014 that was specific to the Microsoft Analytics Platform System, through which you could access data in a Hadoop Distributed File System. With SQL Server 2016 we cut the strings, making it possible to query data in Hadoop, as well as Azure Blob Storage. Now you can combine the results of your…
In the beginning of June, Microsoft released SQL Server 2016. With it, they are delivering an end-to-end data management and business analytics solution with mission critical intelligence for your most demanding applications as well as data insights on any device.
SQL Server 2016 is ideal for:
Mission critical intelligent applications delivering real-time operational intelligence by combining built-in advanced analytics and in-memory technology without having to move the data or impact end-user performance.
Enterprise scale data warehousing with enhanced in-memory column store that increases query performance by over 100x vs disk-based solutions. With SQL Server 2016, you can also access optimized MPP scale-out software that can be combined with scale-out appliance architecture with our Analytics Platform System (APS).
Applications requiring the highest levels of security with new Always Encrypted technology that protects your data at rest and in motion without impacting database performance.
Comprehensive business intelligence solutions on…