Power BI Automation: What Is Your Data Telling You?
Power BI Automation – Every year, Gartner releases technology trends that are vital to businesses. In 2022, the list consists of 12 strategic trends that will allow CEOs to deliver growth, efficiency, and digitization—and position IT executives and CIOs as strategic partners in an organization.
One of those trends that has been and will continue to be a lens through which leaders connect and make informed decisions is data. Gartner calls this overarching drive-through data, the Data Fabric.
2022 Technology Trend 1: Data Fabric
Data fabric is a design concept that acts as an integrated layer of data and connecting process. It uses continuous analytics over existing and discoverable metadata to support the designing, deploying, and use of reusable and integrated data across different environments, including multi-cloud and hybrid platforms.
Simply put, data fabric provides flexible and resilient integration of data sources across platforms and business users, thereby making data available everywhere it is needed regardless of where the data resides. Data fabric can utilize data analytics to learn and proactively recommend areas where data should be utilized or altered. This can help lower data management efforts by up to 70%.
Data fabric has four components, namely:
- Data processing: It curates and transforms data, providing analytics-ready data for AI and BI.
- Data ingestion: It works with data from various sources, including databases, data streams, and cloud source applications. It simplifies stream and real-time data processing.
- Data orchestration: It provides an extensive view of the data pipeline. It also coordinates and helps manage the data flow.
- Data governance: It consolidates all data governance processes and enables local management of data in compliance with corporate and global policies.
What Is Data Fabric Used For?
Think of a data fabric as a weave that’s stretched over a large space connecting multiple locations, sources, and types of data, with methods for gaining access to that data. As data moves within a data fabric, it can not only be processed, managed, and stored, but it can also be accessed by or shared with internal and external applications for various analytical and operational use cases for all organizations–including product development, advanced analytics for forecasting, and sales and marketing optimization.
Ultimately, a data fabric helps your organization leverage the power of data to meet its demands and gain a competitive advantage. It allows your IT team to better use the power of the hybrid cloud, create a hybrid multi-cloud experience, and modernize storage through data management. This is to say that data fabric is not just about storage.
What Problems Does Data Fabric Solve?
A data fabric solves most of the data-related challenges that organizations face. With applications and users’ needs growing, organizational IT systems are becoming more sophisticated. This has given rise to scenarios where one application might be hosted on-premise while another may be deployed on the cloud due to compliance constraints. In such scenarios, organizations are forced to have separate environments to operate across and handle these complex and definite systems.
A data fabric can ensure that an organization supports all disparate environments while continuously providing support for existing applications and services. Each application will have its own approach to how data is stored, retrieved, and accessed. While some applications may use flat files, others may need relational databases or even a big data repository. Needless to say, the difference in data storage type can create data silos, limiting an organization’s ability to access and control data and resulting in security and maintenance issues.
Data fabric can help solve various problems, including:
- Siloed data
- Poor scalability
- Lack of reliability in data security and storage
- Reliance on underperforming legacy systems
Among other ways, it does this by:
- Creating a unified data environment
- Bolstering data preparation, data quality, and data governance capabilities
- Centralizing data flow coordination
- Avoiding data silos
- Allowing easy scalability
Is Data Fabric a Tool?
The primary purpose of data fabric is to create a unified view of data from different sources and to facilitate application access to data, regardless of where the data lives, database association, or structure. Data fabric can also be used to simplify analysis, usually with AI and ML(machine learning). As such, it is becoming a vital tool in converting raw data into business intelligence.
What Is a Data Fabric Example?
An example of a scenario where data fabric comes in handy is in a multi-cloud environment where one cloud, such as Azure, oversees data transformation and consumption and another platform, such as AWS, manages data ingestion. There might be a third vendor, such as IBM, providing analytical services. A data fabric architecture stitches the different environments together, creating a unified view of data.
But this is just one data fabric example. Given that different businesses have different needs, they will also require varying architecture for a data fabric. The different data infrastructure implementations and the various cloud providers create variations on data fabric architecture needs across businesses.
Use Cases of Data Fabric
Data fabric is still in its infancy with regard to its adoption, but its data integration capabilities help businesses in data discovery, enabling them to take on various use cases. Whereas the use case that a data fabric can handle might not be very different from other products, it differentiates itself by the scale and the scope it can handle when eliminating data silos.
By integrating data across various sources, organizations and their data scientists can create a holistic view of their customers—this is particularly helpful in service industry clients such as banking customers. Data fabric has been more specifically used for:
- Fraud detection
- Customer profiling
- Return to work risk models
- Preventive maintenance analysis, and more.
Data From Your Organization Will Continue to Drive Improvement
Today, data is considered to be one of the most valuable resources. Among other things, it can help various organizations make informed decisions. Even so, the data needs to be converted into a useful form for you to get valuable insights from it. This is where Power BI automation comes in—it provides a multi-perspective view into datasets, with visuals that represent different insights and findings.
Automated Power BI Reports like those from ChristianSteven can be delivered across your business, providing the data that you need to grow.
Power BI reporting can help ensure that your team makes the most of the data that your business generates. It not only allows you to access and distribute insights, but also ensures that your team members collaborate and build reports anywhere and at any time.
With that in mind, increase the accuracy and convenience of power BI reporting with Power BI Report Scheduler by ChristianSteven that can automate delivery. Reach out to ChristianSteven to learn more about how their solution can help automate Power BI reports.