Looker vs Power BI: Comparision Of Data Visualization Tools


Looker vs Power BI – Table of Content

What is Looker?

The looker is a kind of enterprise platform which is used for business intelligence and data applications.  The looker provides you the tools that provide power to a multitude of data experience, and embedded analytics to workflow integrations and custom data apps. It provides a unified surface to access the truest and most up to date version of your organization data. It enables analytics anywhere with full customization of the look and feel of data experiences. 

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Why looker?

Looker is a powerful data analytics platform, which can help both the large scale and small scale industries, that glean value from their data. It is a platform that makes collecting, visualizing, and analyzing data a bit simpler. This is browser-based and provides a unique modeling language, and it is simple to use. Its software makes it simple to select, customize, and create a variety of interactive visualizations, which provide a variety of graphs and charts to choose from.

What is Power BI?

It is a collection of software services, connectors and apps, which work together that is helped to turn our unrelated sources of data into coherent, interactive insights, visually immersive, etc. our data can be an Excel spreadsheet, it may be a collection of cloud based, and also the on premises hybrid data warehouses. It lets us simply connect to our data sources, visualize and discover what’s important, and it helps to share that with anyone or everyone you want. It consists of various elements which all work together, starting with these three basics, they are.

  1. Power BI Desktop, which is a Windows desktop application
  2. the Power BI service, which is an online SaaS  service.
  3. And the Power BI mobile apps for Windows, iOS, and Android devices.

Why Power BI?

Its user interface is fairly intuitive for users who are familiar with Excel, its deep integration with other Microsoft products makes it a very versatile self-service tool which requires little upfront training. The free version of power bi is intended for small to midsize business owners. It is used to find insight within companies data. It helps to connect disparate data sets, transform and clean data models. 

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Comparison between Looker and Power BI

Looker VS Power BI

1. Data source connectivity

Looker: The looker may connect to a number of data sources, but the most important feature in it is its own trusted data model. We can get more value from our data, quic with Looker connections. Looker’s Simple configuration makes data available within minutes  and it is all from the Looker UI. We Don’t need to spend weeks or months testing new analytics tools, and create a complete analytics suite inside Looker in under 24 hours.

Power bi: Microsoft power bi supports a lot of data sources, which includes flat files, SQL-based databases, blank query, etc. The Power BI is a self-service Business Intelligence tool, which lets us connect the many different data sources, Power BI provides 92 different data connectors for connecting the data sources. By using these connectors, we may connect to various data sources. It provides two different Data Connectivity modes to connect the data sources and Import and DirectQuery.

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2. Data volume

Looker: Lookers queries designed through the explore page, which will have a maximum limit of 5000 rows. We may restrict the data that we are viewing to items of interest by adding filters. As we might limit the results to particular dates, customers, locations, or anything else, which is the part of our data. the field that is in our Looker instance may become a filter. We don’t necessarily need to add a dimension or measure for our results in order to filter on it. We may design a query which filters the Order Date to just the last 90 days, our query only shows Customer and Number of Orders.

Power bi: Microsoft power bi may handle a maximum of 10 GB of data storage for each use, we can access it directly through the database. All visuals employ one or more data reduction strategies in order to handle the potentially large volumes of data being analyzed. A simple table employs a strategy which is to avoid loading the total dataset for the client. reduction of strategy is being used varies by visual type. Every visual selects from the supported data reduction strategies as part of generating the data request sent to the server. visual controls the parameters on those strategies that is to influence the overall amount of data.

3. Implementation

Power bi: Power bi provides on prem and cloud options available.Businesses look to drive the adoption and productionize Power BI, it maintains numerous architectural and procedural approaches that must be important to cultivate a stable, intuitive, and reliable reporting and analytics ecosystem. To find a balance between enabling self-service and enforcing governance for the tool is important for operating a high value and business-focused Power BI platform.

Looker: The looker is completely the browser based.For large organizations by using many segmented departments, the governance of data becomes a critical task to handle. Looker is a great tool, that is to help with data governance as it provides a rigid data model, and most teams require some flexibility with their data model and need the ability to redefine or add to certain parts of the data model. It may be Hub or the Spoke.

4. Visualization

Power bi: Power bi has a lot of visualization options to choose from. It supports about 3,500 data points. We may personalize the visualization pane by adding and removing Power BI visuals from it. When we remove the default visuals from the visualization pane, We may restore the pane for default and bring back all the default visuals.

Looker: In the looker users can create custom visualizations. It provides extensive visualization abilities with real-time analysis. parameter of the visualization adds a custom visualization to our LookML project, with which customers may access from the Visualization tab in the project’s Explores. Its custom visualization must be defined in a JavaScript file, thay may be included in our LookML project files, or hosted elsewhere.

5. Integration

Power bi: Microsoft power bi may seamlessly integrate with Microsoft tools, and it also has access to salesforce, google analytics, etc. 

Looker: Looker integrated data with many applications like excel and google docs, it blocks feature streamline integrations which offer pre built code, it can be embedded into outside systems with more ease.

6. Querying:

Power bi: Microsoft power bi contains a natural language query tool, at where you may ask questions and get answers. 

Looker: The looker has the language LookML, which is the language to describe dimensions, aggregations, etc.

Data visualization helps your business by delivering data in the most efficient way, no matter what business you choose. During the process of business intelligence, data visualization takes the raw data and delivers the data in raw form, so the conclusions can be reached. It uses visual data to communicate information in a manner, which is effective, fast and universal. It can help companies to identify which areas need improvement, which factors affect customer satisfaction and what to do with specific products. It positively affects an organization’s decision making process with visual representations of the data. There are many visualization tools in the market, the most renowned among them are looker and power BI.

Advantages of Looker

  • Looks allow you to create it for routine focus analysis, and to build a dashboard simply by combining looks. It is simple to share reports by forewarning the link, it is user friendly and enough to democratize data for the entire organization.
  • Looks modify saved reports to highlight specific points of interest, and report across multiple clients, referral objects and lead paths. Look saves reports for real time updates.

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Disadvantages of Looker

  • Looks were tricky to get started, but once we learn how the system organizes and classifies, it gets very simple. Sometimes it takes too long to load and as a result we don’t find the object for which we are looking. 
  • The looker is complicated for users to be able to create their own calculation, as they have to be added to the data model. Very easy tasks look complicated in it.
  • Looker also available as the mobile version which is not similar to caliber as the full version, its usage become complex when conducting unusual processes. The looker requires a lot of time to load the data sometimes.

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Advantages of Power BI

  • Power bi is affordable and relatively inexpensive, its desktop version is free of cost, we can download and start using it to make dashboards and reports on our computer. When we want to use more services and publish reports, we need to subscribe to its plans, which are affordable.
  • It provides a wide range of custom visualizations, made by developers for a specific use. We can use custom visualizations in addition to general visualizations, which includes maps, charts, graphs and script visuals.
  • It allows you to upload and view your data in excel, you can filter data in the dashboard and then put it in excel. You can import data from a wide range of sources, it offers data connectivity to data files like JSON. Excel, azure sources, server databases and online services like facebook, google analytics, etc. 

Disadvantages of Power BI

  • It is good with handling simple relations between tables in a data model, but when there are complex relationships between tables, it might not handle them well.
  • Users have limited options for what they can change in visuals, it provides only few options to configure your visualization as per your requirements.
  • User interface is found crowded and bulky by users. It is the sense that as there are many icons of options, which may block the view of the reports.

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Conclusion

The tool you select is going to be highly dependent on your future goal and your company requirements, before selecting defining the future goals and company requirements is very important. So you need to select the one, which your business requires.

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AWS Edge Locations: A Brief Introduction 

AWS Edge locations are third-party data centers made to ensure minimal latency while delivering services. It is essentially a small setup, located very close to the user using the AWS service to make the responses quick.

When you look at the situation more closely, what’s happening is that when a user is sending a request, instead of receiving a response from the primary server, it routes to the nearest edge location and provides the response from there, making it quick.

For instance, if your data is housed in an S3 bucket in Australia, some of your traffic comes from Canada. In this example, AWS will start caching your data in one of the edge locations in Canada, so when a request arrives from there, it’ll be delivered from the cache edge location in Canada, avoiding the need for the request to come to Australia. As a result, it will lower the latency, resulting in a better excellent user experience.

The Edge location is popular for providing a speedier response to user requests, aiming to minimize access time and delivery delay. They are located in almost all of the world’s major cities and are utilized by CloudFront (CDN) for fast deliveries to end-users to minimize latency.

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Who Uses AWS Edge Locations?

A set of services that use edge locations and are take latency into consideration are:-

CloudFront: It makes use of edge locations to cache versions of the data it provides, allowing the content to be delivered to users more quickly.
Route 53: It delivers DNS responses from edge locations, allowing DNS queries to be resolved more quickly.
AWS Shield and Web Application Firewall: It screens traffic in edge locations to prevent undesired traffic.

Benefits of AWS Edge Locations

Quick Response: With it being located very close to the place the request comes from, the Edge location is able to deliver a fast response as static content is delivered.

Minimal Access Time: Since the edge locations can offer quick response, this directly helps reduce the access time for the user.

Low Latency Rate: Edge location is physically closer to the user than the primary server. Thus, it has a lower latency rate.

Broader Reach: Edge locations, which are often housed in colocation facilities, increase the scope of the AWS network. They have ample bandwidth and connections to other networks and service providers, and this provides AWS with a wide range of connectivity, even domestic ISPs.

Edge Locations In India

Multiple CloudFront edge locations can be found in India. There are approximately 17 such locations– 4 each in Hyderabad and  New Delhi, 3 each in Bangalore and Mumbai, 2 in Chennai, and 1 in Kolkata. Globally, there are approximately 44 AWS edge locations.

Edge Locations Vs. Availability Zones Vs. AWS Regions

AWS Regions

What will happen in the event of unanticipated situations, such as a natural calamity? This problem gets solved by grouping the data centers into Regions, and these Regions are established worldwide to be proximate to business traffic demand.

To begin, AWS offers a variety of data centers across all Regions that provide various computation, storage, and other valuable resources for hosting your apps. Second, a high-speed fiber network connects all of the Regions. AWS effectively manages this network. Finally, all Regions are separated from one another. It ensures that no data can enter or leave your area in a specific Region. The only exception is if you explicitly authorize the movement of such data.

Availability Zones

Availability Zone (AZ) comprises one or more separate data centers in a particular region that provide redundant power supply, network, and connection. These centers are housed in different buildings. Users can operate production apps and databases in Availability Zones that are quickly available, have fault tolerance and are more scalable than single data centers. There are currently 84 Availability Zones spread over 26 geographic regions around the world.

Despite the fact that each Availability Zone is autonomous, they are linked by low-latency connections within a specific Region. Users have enough freedom with AWS to place instances and store data across many geographical regions and multiple Availability Zones within each Region.

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Edge Locations

What if the users are located in various parts of the globe or in locations that are not in your AWS Regions? Luckily, your organization will not need to start building a new data center. As already explained, this problem gets solved with the help of AWS Edge Locations.

Amazon CloudFront is an AWS service that lets you provide information, video, apps, and APIs to clients across the globe. Low latency and high transmission rates are provided via Amazon CloudFront. But the most crucial aspect is that this service makes use of so-called Edge locations to speed up the connection with customers irrespective of their location.

An organization can send content from Regions to a specific set of Edge locations around the world because Edge locations and Regions are independent infrastructure components. This enables both communication and content delivery to be accelerated. At the same time, Amazon Route 53, a well-known domain name service (DNS) on AWS, is running in Edge locations. This ensures reduced latency by directing clients to the proper web pages.

What is AWS CloudFront?

AWS Cloudfront is an excellent content delivery network (CDN) solution that is extremely fast and capable of delivering data to all users across the world with minimal delay.

The crucial aspect here is that your data is highly secure, thanks to a variety of solid security measures and encryption algorithms, and it’s well connected with Amazon Route 53, AWS Shield, and AWS Web Application Firewall, among other things, to defend it from various forms of attacks.

Why Choose Amazon CloudFront?

Let us find out why people prefer AWS CloudFront and why you should also choose the same. We have compiled its many benefits below:

Quick Content Delivery

The Amazon Cloudfront network has more than 200 points of contact, allowing you to deliver content to AWS consumers and users quickly and with minimal latency. Most significantly, it is incredibly accessible to AWS users and customers.

Pocket Friendly

Amazon CloudFront offers a pay-as-you-go pricing structure with a handful of customizable pricing plans to help you save money.

High Security

Amazon CloudFront is among the most secure content delivery networks available, and it can help you secure both your application and your network.

Compatibility with AWS Services

Amazon CloudFront is compatible with other AWS services such as Amazon EC2, Amazon S3, and Elastic Load Balancing.

It assists developers with AWS Cloud Development Kit, various APIs, and log monitoring, and it can simply interface with Amazon Cloudwatch, among other things, making the developer’s job easier.

Will using the edge result in lower-latency access to EC2?

Using the edge locations can potentially result in lower-latency access to EC2 instances. An edge location is a site that CloudFront uses to cache copies of your content, enabling faster delivery to users at any location. While it may not directly improve latency to EC2 instances, utilizing edge locations can help improve latency to certain AWS services.

To fully resolve any latency issues, it would be beneficial if AWS were to establish a new region in Africa. AWS regions consist of multiple availability zones, each functioning as a separate datacenter and providing low-latency connectivity within that region. By having a region in Africa, users in the continent would experience improved latency when accessing AWS resources.

It is important to note that edge locations primarily serve requests for CloudFront, which is a content delivery network (CDN). CDN technologies aim to reduce latency by caching static content closer to end users. In combination with AWS CloudFront, edge locations help optimize content delivery and provide low-latency connectivity.

While edge locations play a crucial role in delivering content efficiently through CloudFront, AWS Route 53 is responsible for DNS services. Requests made to CloudFront or Route 53 are automatically routed to the nearest edge location, ensuring low latency regardless of the user’s location.

Is the edge just a way to speed up services’ frontends or the services themselves?

The edge serves as a means to enhance the performance of both service frontends and the services themselves. It allows for improved access to various AWS services, which includes an extensive range of options. While it can potentially enhance latency to certain services, it does not solely focus on speeding up frontends. To truly address latency issues, the deployment of a new AWS region in Africa would be most beneficial.

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What does “access services located at AWS” mean in this context?

In this context, the phrase “access services located at AWS” refers to the ability to utilize and make use of the various services available on the Amazon Web Services (AWS) platform. AWS offers a wide range of services for computing, storage, databases, networking, security, analytics, machine learning, and more. By accessing these services, users can leverage the capabilities and functionalities provided by AWS to meet their specific requirements.

It is important to note that there are numerous AWS services available, with hundreds of options to choose from. These services cover various aspects of cloud computing and cater to different business needs. Examples of AWS services include Amazon S3 for scalable storage, Amazon EC2 for virtual servers, Amazon RDS for managed databases, Amazon Redshift for data warehousing, AWS Lambda for serverless computing, and many others.

While accessing different AWS services can offer potential benefits, such as improved efficiency and flexibility, it may not necessarily address latency issues directly. Latency refers to the time delay experienced when transmitting data over a network, and accessing AWS services on their own may not have a significant impact on improving latency.

To address latency issues more effectively, an ideal solution would be the deployment of a new AWS region in Africa. A region in closer proximity to the users in Africa would minimize the distance data needs to travel, reducing latency and improving the overall performance of AWS services for users in that region.

Can S3 objects be cached via Edge locations?

Yes, S3 objects can be cached via Edge locations using CloudFront. Although S3 itself does not have the direct capability to cache objects, CloudFront, which is a content delivery network (CDN) service provided by Amazon Web Services (AWS), can be used to cache and distribute S3 objects to Edge locations.

CloudFront acts as an intermediary between S3 and the end users accessing the objects. When a user requests an S3 object, CloudFront checks if it already has a cached copy of that object in one of its Edge locations. If the object is found in the cache, CloudFront delivers it directly from the Edge location, resulting in reduced latency and improved performance. If the object is not in the cache, CloudFront retrieves it from the S3 bucket, stores it in its cache, and then delivers it to the user.

By caching S3 objects via CloudFront’s Edge locations, the objects become readily available at locations closer to the end users, reducing the need for requests to be sent back to the S3 origin server. This not only improves the overall performance and responsiveness of accessing S3 objects but also helps mitigate network congestion and latency.

Can Route 53 automatically route to Edge locations based on latency?

Route 53 does not have the capability to automatically route to edge locations based on latency. While Route 53 does offer various routing policies that can be configured based on different factors such as geographic location, latency, and weighted distribution, it does not specifically route based on latency to edge locations. It’s important to note that low latency does not necessarily imply the proximity of the nearest edge location. If you would like to understand more about how Route 53 works and the different types of records it supports, I can provide you with more information on that as well.

What services do Edge locations serve requests for?

Edge locations serve requests for CloudFront and Route 53. CloudFront is a globally distributed content delivery network designed to deliver content with low latency, high transfer speeds, and high availability. It acts as a cache, storing frequently accessed content and serving it from the closest edge location to the end user, regardless of their geographical location. Route 53 is a highly scalable and reliable DNS (Domain Name System) service that routes end user requests to the appropriate resources, such as websites or applications, based on the domain name. By leveraging edge locations, both CloudFront and Route 53 ensure that requests are automatically routed to the nearest edge location, resulting in reduced latency and providing a high-performance experience to end users, regardless of their location.

In A Nutshell

These AWS edge locations provide consumers with stable network connectivity, reduced latency, and maximum throughput. Are you wondering if you have ever made use of AWS edge location? You probably have if you have ever used AWS or are an AWS customer. Services like CloudFront and Route 53 already provide edge location benefits, which means you have directly or indirectly used AWS edge locations. So, next time you see a quick response, you know who to thank for it.

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