PowerBI is a business intelligence platform, frequently deployed as part of Azure implementations, which enables business users to gather and display their data in easily interpretable charts and graphs.Ìý

Today, it’s commonplace for firms to expect their users to self-serve. Tools like PowerBI put the power to manipulate and predict outcomes from data right at users’ fingertips. PowerBI connects to a range of disparate data sources (including Excel, CSV, and JSON), before running reports on the data and producing insights in a user-friendly dashboard.Ìý

With regularly updated cloud capabilities, PowerBI provides data analysts with real time dashboard updates, making it easier to spot valuable trends and insights and make data-driven decisions. One of the benefits of PowerBI is its user-friendly interface, making it easier for data stewards to self-serve in data aggregation and analysis. The interactive dashboards, with tile displays and drag and drop functionality, allow users to integrate various datasets into a standardised format, before producing reports to be used in forecasting and decision making.

What is Power BI used for?

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What alternatives are available?

Business intelligence and data visualisation specialists and are two of the biggest alternatives to PowerBI as featured in section dedicated to Analytics and Business Intelligence Platforms.Ìý

Ä¢¹½¶ÌÊÓƵ provides pre-built templates for all three, enabling rapid creation of dashboards to help improve the health of data in an organsation and win data quality management business cases at senior decision-making levels. Contact us to find out more.

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Data profiling is an essential component in maintaining data quality. Through running a diagnosis of the data, including its sources and metadata, errors and inconsistencies can be picked up on and amended before becoming actionable intelligence. This helps organizations to understand their data better and take action to improve data quality.

What are the different types of data profiling?

Data profiling can be broken down across structure, content and relationship discovery as follows:

• Structure Discovery:ÌýExamining the data to ensure consistent formatting.
• Content Discovery: AÌýcloser look at the contents of the data, checking for gaps or anomalies in the data itself.
• Relationship Discovery– Investigating how the data relates to other datasets.

What about data profiling by source?

There are different types of profiling by source, which can be categorized by data source, data warehouse, or data management.

• Data sourceÌýidentifies issues with the structure or content of data coming from an external source.
• Data warehouse analyses the data that is stored in a data warehouse.
• Data managementÌýassesses the way data is managed within an organization.

How about profiling within the data itself?

This can also be broken down into three types of pattern discovery: column profiling, row profiling and cell profiling.

• Columns assess the data in each column, looking for patterns and relationships.
• Rows assess the data in each row, looking for errors and inconsistencies.
• Cells assess the data in each cell, looking for completeness.

What are the steps of data profiling?

The first step is to understand the business needs, second to identify the target data, third to collect the data, fourth to analyze the data, fifth to document findings, and lastly to resolve issues.Ìý

Through this process, organisations can prevent costly data quality errors, which Gartner describes as Moreover, it feeds into the process of data migration, as data needs to be cleansed and profiled before it’s moved into a new location.

What is data migration?Ìý

Data migration is the process of moving data from one location to another. This can be done for a variety of reasons, such as upgrading to a new database or moving to a new server. In order to ensure that data is migrated successfully, it is important to have a plan in place. This plan should take into account the various types of data that need to be moved, as well as the potential risks involved. Additionally, it is important to have a backup plan in place in case data is lost during the migration process. By taking these steps, you can help ensure that data migration is done smoothly and without any issues.

How can Ä¢¹½¶ÌÊÓƵ help with data profiling?

This is a core component of Ä¢¹½¶ÌÊÓƵ’ Self-Service Data Quality platform. Every project, programme or tactical exercise starts with profiling to help shed light on exactly what data our clients are dealing with. As many data leaders confess to not knowing what’s in their data, or indeed where it is, profiling is an essential step for us to support our customers in delivering end-to-end perfected data across the enterprise.