32-bit Excel and 64-bit SQL Server

32-bit Excel and 64-bit SQL Server
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What could be simpler than to get data from an Excel table in SQL Server?

There are many ways to accomplish this task. You can utilize Integration Services (former DTS) or import and export wizard, which is the same under the hood. Another way is to create a simple ADO.NET app. You can use the Linked Server mechanism, which allows you to see any ODBC / OLE DB-reachable object in the form of a table (a collection of tables) or the result of an ad hoc query.

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Working with SQL Server in Hybrid Cloud Scenarios. Part 2

Working with SQL Server in Hybrid Cloud Scenarios. Part 2
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As a rule, impersonal information is stored in a public cloud, and the personalized part – in a private cloud. The question thus arises – how to combine both parts to return a single result at a user’s request? Suppose there is a table of customers divided vertically. The depersonalized columns were included in the table located in Windows Azure SQL Database, and columns with sensitive information (e.g., full name) remained in the local SQL Server. Both tables must be linked by the CustomerID key. Because they are located in different databases on different servers, the JOIN statement will not work. As a possible solution, we have considered the scenario, when the linkage was implemented on the local SQL Server. It served as a kind of entry point for the applications, and the cloud-based SQL Server was set up on it as a linked server. In this article, we will consider the case when both, the local and cloud servers, are equal in terms of the application, and the data merging occurs directly in it, i.e. at the business logic level.

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Working with SQL Server in Hybrid Cloud Scenarios

Working with SQL Server in Hybrid Cloud Scenarios
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A hybrid cloud is a fairly attractive model when implementing cloud computing in enterprise information systems since this approach combines the advantages of public and private clouds. On the one hand, it is possible to flexibly attract external resources when needed and reduce infrastructure costs. On the other hand, full control over data and applications that the enterprise does not want to outsource remains. However, in such a scenario, we inevitably face the task of integrating data from various sources. Suppose there is a table with customers, which is vertically divided into two parts. The depersonalized part was allocated in a public cloud, and the information personalizing the customers remained in a local database. For holistic processing inside the application, you need to combine both parts by CustomerID. There are various ways to do this. Conventionally, they can be divided into two large categories: data aggregation at the on-premise database server level which, in this case, will be a single sign on for accessing local and remote data, and data aggregation within the business logic. This article will consider the first approach.

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