Looker and Power BI are popular Business Intelligence (BI) platforms that help to accelerate digital transformation with data-driven decisions. Although the two tools seem to be similar, they have come with notable differences. Well! If you are curious to know the comparison between the tools, you have come to the right place. Here, we have compared Looker and Power BI from many angles that will help you know them better.
Be it a race or battle, those who choose the right strategy will win. On that note, choosing the correct tool before beginning a software project is most important. The critical question is how to choose the best one when two tools seem to be the same. The answer is that you must thoroughly understand the tools from every aspect. This way, Looker and Power BI are business intelligence tools that seem to be similar, but they have their own salient features, pluses and minuses, and differences. This blog compares the two tools from every angle and helps you know the right one based on your needs.
Know that Looker and Power BI are the BI tools that help to create visual analytics, reports, and insights from organized and unorganized data. Looker is part of Google Cloud, whereas Power BI is a product of Microsoft. Here, we analyze Looker and Power BI in terms of their features, pros and cons, similarities, and key differences.
Looker vs Power BI - Table of Content
Looker is one of the business intelligence platforms that provide users with data visualizations, reports, embedded analytics, and helpful insights. It is a flexible, multi-cloud platform that easily scales with growing business needs. It has an analytics-oriented application server that accesses, processes, and then acts on data to derive meaningful insights. Additionally, Looker has a simple User Interface for exploring data and an API for connecting data with other systems.
Know that Looker adapts Machine Learning (ML) capabilities to analyze data and provide the best data experience to users. Looker integrates with workflows and embeds into third-party systems. Not just that, it empowers companies to build their data applications effortlessly. Looker generates valuable insights that will help to improve productivity, make informed decisions, and drive innovation effortlessly while at the same time providing robust security to data. Besides, you can schedule and automate the delivery of insights, reports, and query results to teams. Looker sends alerts to individuals and teams when there is any change in the systems.
Who can use Looker?
Software, Retail, Media, Entertainment, Telecom, and Financial services companies use Looker to analyze their business data and achieve the best data experience. Mainly, mid-size companies use Looker widely.
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Looker comes with many remarkable features. Let’s discuss them below:
Dashboards and Data Visualizations: Looker offers an interactive and dynamic dashboard. It allows users to set alerts, filter, and drill down data to get their desired information. Besides, Looker allows you to choose data visualization models from the data visualization library.
Embedded Analytics: Looker can be embedded into websites, applications, and internal portals with the support of APIs, Looker Blocks, and Looker SDKs. Embedded analytics supports product managers, data analysts, and developers to create custom applications quickly. As a result, they can get insights about workflows accurately.
Looker Security: With Looker’s robust security features, administrators can have more control over databases to manage access to databases effectively. Looker provides the security feature, AES 256-bit encryption, which helps to secure database connection credentials effectively. Even you can secure cached data with this encryption method. Moreover, Looker offers users authentication and data governance capabilities to help them ensure GDPR, SOC type-2, and HIPAA compliances.
Looker Blocks and Actions: Looker blocks are nothing but pre-built pieces of code. In other words, they are pre-built analytical templates. They help to convert data into analytics within a short time. No wonder Looker comes with over 100 blocks. To name a few – SQL patterns, custom visualization, customized analytics, data models, demographic data, data source connections, and embedding capabilities are a few Looker blocks. Another component, Actions, helps to add capabilities to Looker from third-party tools such as – Slack and Marketo.
LookML and Data Modeling: LookML is the SQL Based modeling language of Looker. You can use this language to create an ML model based on business logic. This model is updated whenever there is a change in the business logic. Overall, data modeling with Look ML provides you with consistent, accurate, and real-time analysis of your data.
Looker API: Looker offers a secure and RESTful API for customizing the Looker platform as well as connecting with the data of different sources. With this API, you can create custom applications and data-driven workflows. Further, you can automate the tasks such as creating new Looker accounts, scheduling reports, running queries, and embedding insights into other applications.
Looker Extension Framework: Essentially, the Looker extension framework is a fully-hosted platform. It supports developers in building workflows and data-powered applications. With this framework, you can build web applications with features such as access control, authentication, and API access.
To wrap it up, Looker is good in data modeling, filtering, embedded analytics, and making deep analyses at a granular level. On the other side, Power BI is good in terms of security, scalability, extensibility, and mobile capabilities. Both tools come with many pluses and minuses. This is a simple but important note that the excellent choice depends on the requirements of users. They must thoroughly review the features of the two platforms and choose the one that will best meet their requirements.
Advantages of Looker:
Drawbacks of Looker:
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Power BI is yet another powerful, scalable, and unified BI platform. It is an all-in-one platform for creating both self-service and enterprise analytics. Power BI acts on organized and unorganized data, including texts and images, and converts them into meaningful data through detailed reports, visual analytics, and helpful insights. Not just that, you can share the derived data with other applications seamlessly. In a way, Power BI lessens the gap between data and decision-making as low as possible and allows you to make concrete decisions.
Know that Power BI is available on Desktop, Cloud, and Mobile platforms. The crucial thing about Power BI is that it offers a self-service option, which allows users to personalize dashboards based on their needs. Power BI integrates with other Microsoft products, such as Power Apps and Power Automate platforms, for building applications and automating workflows.
Who uses Power BI?
Power BI can be used in small to medium to large-scale enterprises. For example, it is used across energy, manufacturing, retail, media, etc. Business users, Analysts, and Developers use Power BI to monitor and analyze their business processes and workflows.
Are you still wondering why Power BI is considered one of the most effective BI tools? Let’s read the below to know more.
Data Visualizations: Power BI easily converts complex data into comprehensible and understandable data with colorful visualizations. No doubt, it allows you to make informed decisions confidently. Know that Power BI offers hundreds of data visualization models you can get from the visualization library. You can also tailor the visual models per your needs and share them with the Power BI community.
Embedded Analytics: No wonder you can embed Power BI in any application. You can embed Power BI reports, dashboards, and analytics into any application. As a result, you can get insights, personalized reports, and analytics and make accurate and concrete decisions. You can automate monitoring, deploying, and managing embedded analytics in applications at the same time without losing control over the Power BI features.
Integration with Excel: You can achieve comprehensive and excellent data analytics and visualization by integrating Power BI with Microsoft Excel. This integration allows you to display multiple charts and tables on the Power BI dashboard. Also, Power BI allows you to create interactive dashboards through which you can ask queries in natural language and get responses. Even excel beginners can interact with dashboards effortlessly. Besides, you can get advanced analytics and insights by running R scripts and with the support of R-powered custom visuals.
Security: Power BI ensures security to your data – whether inside or outside the organization. With its intelligent data protection capabilities, Power BI ensures data protection by responding to risks as soon as possible. The integration of Power BI with the Microsoft Cloud App Security portal quickly identifies risky patterns in the data and sends alerts to users. No surprise that Power BI helps to meet compliance requirements for more than 100 security standards, including HIPAA and FINRA. What's more! Power BI supports reducing network risks through robust permission controls and Virtual Private Networks (VPNs).
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Advantages of Power BI:
Drawbacks of Power BI:
Of course! There are a few shortcomings of Power BI.let’s take a look at them.
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Undeniably, Looker and Power BI are identical in many ways. Let’s see what they are.
The main question is, what are the key differences between Looker and Power BI? Let’s discuss the same below:
Installation: Looker is an entirely browser-based tool offered only in the Cloud platform, whereas you can install Power BI on Desktops, on-premises, and mobile devices.
Data Modeling: Looker uses LookML data models for data modeling. You can either build your own lookML model based on your business logic or use the pre-built LookML models. On the other hand, you can build a data model in Power BI by defining relationships between tables of databases. And you can use power query, DAX language, or use source data for making data modeling in Power BI.
Data Processing, Looker processes a large volume of data because of its scalability and extensibility. Power BI struggles to handle large datasets. It uses Cloud services and databases when the data size exceeds 10 GB.
Interactive Dashboards: As you know, both Looker and Power BI provides interactive dashboards. However, Power BI allows you to create self-service dashboards. It means that you can create your dashboards based on your needs in addition to the enterprise dashboard.
Ease of Query tools: Looker uses LookML for querying, which demands some technical knowledge. On the other side, Power BI uses a natural language querying tool that is easy to use.
Platform Support: Power BI supports Desktop, Cloud, and Mobile versions. On the other hand, Looker offers only the Cloud version. It doesn’t support on-premises and mobile versions. Also, Power BI works well with Windows operating system but doesn’t work with macOS. If you want to run Power BI in macOS, you must run it only with Virtual Machines.
Integration: Looker uses Looker Blocks to connect with data sources quickly. With Looker Blocks, you can quickly make data available in dashboards. In other words, you can quickly create analytics and reports. On the other hand, Power BI doesn't use anything like blocks. Still, it effectively integrates with Microsoft products such as power apps and Power automate, Google analytics, salesforce, etc., to build applications and automate workflows.
Security: Looker secures data through efficient authentication, monitoring, and encryption. On the other side, Power BI ensures security through sensitive labeling, end-to-end encryption, Microsoft Cloud App security, and real-time access monitoring.
Below is the Google trend about Looker and Power BI. You can see that Power BI is getting interested among people over time.
To wrap it up, Looker is good at data modeling, filtering, embedded analytics, and making deep analyses at a granular level. On the other side, Power BI is good in terms of security, scalability, extensibility, and mobile capabilities. Both tools come with many pluses and minuses. This is a simple but important note that the excellent choice depends on the requirements of users. They must thoroughly review the features of the two platforms and choose the one that will best meet their requirements.
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Keerthi Sai is a Senior Writer at Mindmajix with tons of content creation experience in the areas of cloud computing, BI, Perl Scripting. She also creates content on Salesforce, Microstrategy, and Cobit.
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