Unlock Insights with Azure Time Series Database

Azure Time Series Database is a game-changer for businesses looking to unlock valuable insights from their data. It's designed to store and process large amounts of time-stamped data, making it perfect for applications like IoT, industrial monitoring, and predictive maintenance.

With Azure Time Series Database, you can store data at a rate of up to 10,000 events per second, and scale as needed to handle large volumes of data. This makes it an ideal solution for businesses with high-volume data streams.

Data is stored in a column-family format, which allows for fast querying and aggregation of time-series data. This means you can quickly analyze and visualize your data to gain deeper insights into your business.

By leveraging Azure Time Series Database, businesses can improve operational efficiency, reduce costs, and make more informed decisions.

To get started with Azure Time Series Insights, you'll need to provision an Azure Time Series Insights Gen2 environment. This is the foundation for your time series database.

You'll need to provide data access to the environment, which can be done by adding users or groups with the necessary permissions. This allows others to access the data as well.

To start collecting data, you'll need to add an event source to the environment. This can be done by following the Azure Time Series Insights Gen2 tutorial.

Here's a quick rundown of the prerequisites:

By following these steps, you'll be well on your way to setting up your Azure Time Series Insights database and starting to collect and analyze your time series data.

Azure Time Series Insights is a game-changer for real-time data analysis.

You can easily ingest, model, query, and visualize fast-moving time-series data generated by IoT devices using Azure Time Series Insights.

Real-time data from devices like mobile devices, sensors, satellites, and medical devices can be fetched to the Azure environment using Azure IoT Hub.

Azure IoT Hub acts as a data integration pipeline to connect to the source devices and deliver data to the TSI platform.

Once the data is in the TSI, it can be used for visualization purposes and queried and aggregated accordingly.

Users can leverage existing analytics and machine learning capabilities on top of the data available in TSI.

Data from TSI can be further processed using Azure Databricks and machine learning models can be applied based on pre-trained models that offer predictions in real-time.

Using Azure TSI, users can easily visualize aggregated data using line charts or heat maps.

Azure Time Series Database offers two pricing models: the Per-GB model and the Reserved Capacity model.

The Per-GB model charges you for the amount of data stored in the database, with a cost of $0.50 per GB per month.

For the Per-GB model, you only pay for the data you store, making it a cost-effective option for small to medium-sized time series datasets.

Data transfer costs an additional $0.12 per GB for the first 10 TB of data transferred out of Azure per month.

Reserved Capacity provides a significant discount for large-scale time series datasets, with a cost of $0.25 per GB per month.

Reserved Capacity requires a one-year or three-year commitment, and you can cancel at any time after the commitment period ends.

With Reserved Capacity, you can also save on data transfer costs, which are reduced to $0.06 per GB for the first 10 TB of data transferred out of Azure per month.

You can use the Azure Pricing Calculator to estimate your costs and compare the two pricing models.

The environment panel in Azure Time Series Insights Gen2 is where you'll find all the environments you have access to. It's a one-stop shop to manage your environments.

You can select the environment you want to use and be taken there immediately. This makes it easy to switch between different environments.

The environment panel displays both Gen2 and Gen1 environments, so you can easily navigate between them.

You can use the environment panel to analyze your time series data, chart it, and perform rich analytics. This is a powerful tool for getting insights from your data.

The Model option in the environment panel allows you to push new types, hierarchies, and instances to your Time Series Model.

If you're working with an existing Gen1 environment, you might want to use the Gen1 product and Gen2 product in combination. This is especially useful if you're trying to get the full UI experience for a Gen1 environment.

The Gen1 environment controls are available in the updated UI, and they include some functionality from the existing UI. However, if you want the full UI experience for a Gen1 environment, you can use the new Azure Time Series Insights Explorer.

The hierarchy tree and search panel in Azure Time Series Insights Gen2 is a powerful tool for navigating and finding specific time series instances. You can easily search and display instances on your chart.

The search results pane offers two views: hierarchy and list. This makes it easy to find the instances you want to display, whether you prefer a visual or straightforward list.

You can add selected instances to the current chart and also to the data well, making it simple to work with multiple data sets.

Azure Time Series Insights Gen2 is an open and scalable end-to-end IoT analytics service. It's designed for ad hoc data exploration and operational analysis.

You can use it to collect, process, store, query and visualize data at Internet of Things (IoT) scale. This includes data that's highly contextualized and optimized for time series.

Its powerful capabilities can be integrated into your existing workflow or application using rich APIs. This makes it a flexible offering that meets the broad needs of industrial IoT deployments.

Data collected and analyzed with Azure Time Series Insights Gen2 is highly contextualized and optimized for time series. This allows you to uncover hidden trends, spot anomalies, and conduct root-cause analysis.

Model Authoring is a crucial aspect of working with Time Series Models. You can perform full CRUD operations on your Time Series Model in Azure Time Series Insights Gen2.

Time Series Model types allow you to define variables or formulas for computations. They're associated with a given Time Series Model instance and can have one or more variables.

Hierarchies are systematic organizations of your data, depicting relationships between different instances in your Time Series Model.

Instances are the time series themselves, often represented by DeviceID or AssetID, which is the unique identifier of the asset in the environment.

The hierarchy and search functionality is a game-changer for navigating complex data models.

You can easily search and navigate your Time Series Model hierarchy to find the specific time series instances you want to display on your chart.

The hierarchy tree allows you to do just that, making it simple to locate the data you need.

Selecting your instances not only adds them to the current chart but also adds them to the data well.

The search results pane is also quite useful, offering a hierarchy view or a list view to help you find the instances you want to display.