Microsoft Ads is a well-known advertising platform that places your ads in front of the Microsoft network to increase awareness, engagement, and sales. While Microsoft provides metrics and analysis of Microsoft Ads data, decision-makers want to compare the insights of their online marketing campaigns to other marketing efforts and the overall performance of their company. Microsoft Advertising to Redshift Integration takes minutes, allowing you to concentrate on analyzing your ad spending and performance data.
This post will walk you through the process of syncing your Microsoft Advertising data to Amazon Redshift. By doing so, you will be able to perform advanced analytics on a system designed for such data payloads, such as Amazon Redshift.
What is Microsoft Advertising?
Microsoft Advertising (previously Bing Ads, Microsoft adCenter, and MSN adCenter) is a pay-per-click advertising solution available on the Bing, Yahoo!, and DuckDuckGo search engines. Bing Ads has a 33 percent market share in the United States as of June 2015.
The Microsoft Ads API provides programmatic access to Microsoft Advertising for marketers that place a large number of ads or developers who construct advertising applications. The Microsoft Ads API is the most effective approach to handle many large campaigns or combine your marketing with other internal systems.
The Microsoft Ads API also supports multiple customer accounts, making it simple for ad agencies to handle campaigns for a large number of clients. Some firms may take a hybrid strategy, using the web UI for most functions but leveraging the API to automate reporting or campaign optimization.
Key Features of Microsoft Advertising
Here are some features of Microsoft Advertising:
- Shopping Campaign Reporting Enhancement: Microsoft Ads has released two new additions to Shopping Campaigns reports, giving users a greater view of the performance of their products. The first edition is called “Performance,” and it includes information on impressions and clicks, as well as average costs and spending. The second improvement is “Conversions,” which displays the revenue, return on ad spend (ROAS), and all conversion data.
- No Minimum Spend Requirement: The functionality is useful for remarketing programs since it allows marketers to upload their customers’ email addresses and reengage with them on numerous platforms that use the Microsoft Search Network and the Microsoft Audience network.
- Expansions of the Audience: Audiences are also available as betas in the United Kingdom, Australia, India, New Zealand, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. This enables marketers to easily engage with prospective customers that share similar interests and habits as the brand’s remarketing list.
- Increasing Search Imagery: Microsoft plans to differentiate itself by exploiting imagery and what they call “visually immersive upgrades” to the advertising experience for its customers, both consumers, and advertisers, with a new focus on visual narrative.
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What is Amazon Redshift?
Amazon Redshift is an Amazon Web Services-powered petabyte-scale data warehouse system. Because it facilitates data administration, it is also utilized for massive database migrations. The architecture of Amazon Redshift is built on Massively Parallel Processing (MPP). Amazon Redshift Databases are Column-Oriented Databases that may be connected to SQL-based clients and BI tools. This provides users with continuous access to data (structured and unstructured) and facilitates the execution of Complex Analytic queries. Amazon Redshift also supports standard ODBC and JDBC connections.
Amazon Redshift is a fully-managed Data Warehouse, customers may automate administrative chores so that they can focus on Data Optimization and Data-driven Business decisions rather than doing repetitive tasks.
Key Features of Amazon Redshift
Amazon Redshift has the following features:
- Integrated Analytics Ecosystem: AWS’s built-in ecosystem services simplify End-to-End Analytics workflow management while avoiding compliance and operational stumbling blocks. AWS Lake Formation, AWS Glue, AWS EMR, AWS DMS, AWS Schema Conversion Tool, and others are some well-known examples.
- SageMaker Support: It enables users to construct and train Amazon SageMaker models for Predictive Analytics utilizing data from their Amazon Redshift Warehouse, making it an essential tool for today’s Data Professionals.
- ML for Maximum Performance: Amazon Redshift features powerful Machine Learning (ML) capabilities that allow for high throughput and speed. Its advanced algorithms predict forthcoming questions based on specific factions, allowing vital tasks to be prioritized.
Introduction to Microsoft Advertising to Redshift Integration
Microsoft Ads is a robust advertising platform with an API that allows you to connect with it programmatically and get analytics and reports on the performance of your campaigns. You’ll be interested in this Microsoft Advertising to Redshift Integration in this piece.
Step 1: Use Microsoft Ads to Access Your Data
The first step in importing your Microsoft Advertising to Redshift is to gain access to it and begin extracting it. Microsoft Ads features a robust API for connecting with the platform as well as creating and running campaigns programmatically. A significant component of the API is a robust reporting system that assists you in understanding how the campaigns you run perform.
The default setting is “Summary,” which means you’ll get a report for the duration of your account. It is recommended that the aggregate be set to daily for analytic reasons. This is also the smallest time granularity available in Microsoft Ads. Because the Microsoft Ads API is developed using the SOAP protocol, your development will be more complicated because you will have to manage SOAP and XML answers. Also, like with any other API, you must adhere to the API usage limits and ensure that failures are handled correctly. Reports in Microsoft Ads are created by selecting the following options:
- Columns, the columns you want to see in the report
- Custom filters should be provided to filter the report data.
- Scope, to narrow down the info you receive based on specified accounts.
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Step 2: Prepare and Transform Your Microsoft Ads Data
After you have obtained your data for Microsoft Advertising to Redshift, you must change it based on two major variables,
- The constraints of the database into which the data will be loaded
- The type of analysis you intend to do
Each system has its restrictions on the data types and data structures that it can support. If you wish to push data into Google BigQuery, for example, you can transmit nested data like JSON directly, but keep in mind that SOAP APIs like Bing Ads return XML answers.
Instead, like with JSON, you will need to flatten your data before loading it into the database. You must also select the appropriate data types. Again, depending on the system to which you will transmit the data and the data types exposed by the API.
Step 3: Prepare and Transform Your Microsoft Advertising to Redshift
Amazon Redshift is based on industry-standard SQL and includes features for managing very big data sets and doing high-performance analysis. To put your data into it, you must adhere to its data model, which is a normal relational database schema. The data from your data source should be organized into tables and columns.
Designing a schema for Microsoft Advertising to Redshift and mapping data from your data source to it is a serious procedure that can affect both the performance of your cluster and the questions that you can answer. It’s always a good idea to keep in mind the best practices for designing a Redshift database that Amazon has released.
When you have decided on the design of your database, you must load it onto one of the data sources Microsoft Advertising to Redshift, which is as follows:
- Amazon S3
- Amazon DynamoDB
- Amazon Kinesis Firehose
Step 4: Fill Amazon Redshift with your Microsoft Ads data
To upload your data from Microsoft Advertising to Amazon S3, you must utilize the AWS REST API; as we can see, APIs play a key part in both data extraction and data loading into our data warehouse. The first task is to create a bucket, which you do by executing an HTTP PUT on the Amazon AWS REST API endpoints for S3.
Microsoft Advertising to Redshift has two techniques for importing data into it. The first is by issuing an INSERT command. You can use your client to connect to your Amazon Redshift instance using a JDBC or ODBC connection, and then conduct an INSERT command for your data. The INSERT command is invoked in the same way as any other SQL database; for additional details, see the INSERT examples page in the Amazon Redshift documentation.
Microsoft Advertising to Redshift is not designed for INSERT-like operations; rather, bulk uploads using a COPY command are the most efficient way of adding data to it. You can use the COPY command to copy data from S3 flat files or an Amazon DynamoDB table. When you issue COPY instructions, Amazon Redshift may read many files at the same time and intelligently distributes the burden across the cluster nodes, allowing the load to be performed in parallel.
Benefits of Microsoft Advertising to Redshift Integration
- Transform any data without using SQL: Simply link Microsoft Advertising to Redshift to begin building data pipelines faster—no coding necessary. Anyone comfortable with Excel can construct scalable data pipelines in Amazon Redshift.
- Centralized Centre: You may take data from Microsoft Ads, transform it, and load the findings to Amazon Redshift easily. Accelerates decision-making and allows you to swiftly implement optimizations without wasting time processing data.
- Spending it Right: If your company spends a lot of money on Microsoft Ads, having accurate and up-to-date data insights from your Bing Ads accounts is critical. You can begin collecting analytics-ready data into your Redshift cloud data warehouse with only a few clicks.
So far, we’ve just scratched the surface of what Amazon Redshift can accomplish and how to load data into it. The path to take is strongly dependent on the data you wish to load, the service from which it is coming, and the needs of your use case.
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