24.09.2022 | Nikolay Valiotti
Clickhouse: Overview and Applications
Analyzing data, finding answers, unlocking insights—all these tasks start with a data analytics stack. In order to take your data from its source all the way through analysis, you need a certain set of technologies. In one of the layers of your data analytics stack, there should be a business intelligence tool like Looker.
Looker helps companies explore, share, and visualize their data. But there is a lot more to uncover about this tool, and we’ll try to answer a few questions:
Looker aims to deliver data experiences that support all the ways modern businesses make decisions. It does so with these core features.
LookML is the secret sauce to the entire platform: a powerful SQL-based modeling language. A data modeler just needs to understand the basic concepts of creating projects and developing in Looker to write LookML.
The language is used to describe dimensions, aggregates, calculations, and data relationships in a SQL database, using a DRY (don’t repeat yourself) style. In other words, Looker uses SQL expressions repeatedly, removing technical skills as a potential barrier. So, business users won’t have to deal with the complexities of SQL structure.
Looker (PBL), Looker’s embedded analytics functionality, makes sophisticated analytics easy and fast. It makes it possible for data analysts, product managers, and developers to create custom applications or insert analytics into existing apps, websites, and portals.
By embedding analytics, you can build a self-service environment for users and provide real-time insights to customers and suppliers.
The Looker data visualization tool helps create interactive and dynamic representations of data for individuals or groups. A single dashboard can even bring multiple experiences, depending on how they filter them—for sales reps, customer success managers, or external viewers.
You can choose from a library of production-ready visualizations. Here are a couple of Looker example dashboards:
If you’re looking for something even more specific, you can also create your own visualizations and dashboards.
Manage your Looker instance and fetch data through the Looker data platform in a secure, “RESTful” programming interface. Anything you can do in the Looker application is available via the Looker API—creating new user accounts, running queries, scheduling reports, etc.
Consider using an SDK instead of making manual requests to the API. The official Looker API client SDK is available in several languages:
The latest Looker analytics platform update, Looker 21, has brought out new features and configurations. These are some of the highlights that allow data teams to go beyond reports and dashboards.
This is a one-stop hub for the Looker developer community, where you can find information on everything from exploring data (Looker pivot, field picker, etc.) to custom fields (Looker bins, Min/Max/Medium, etc.) and functions for dbt and LookML (dbt utils star, order by field, etc.).
All overview guides and tutorials are free and continuously updated.
This feature brings the filters to a dashboard, allowing analysts who are working in Looker to handle customization on their own. With the decreased application maintenance and overhead for developers, you’ll let them focus on other tasks and speed overall development.
Understand your Cloud spending across AWS, Azure, and Google Cloud Platforms with a granular look. View and analyze how different teams within your organization are spending on certain projects, teams, and resources. Real-time cross-platform insights are centralized into one data point.
The Looker Retail Analytics Block is designed specifically for retail organizations, bringing forward key data:
The Looker mobile application has brought the much-needed functionality to view Looks and dashboards and browse content stored in folders. You can also change filter values and add/remove dashboards from your favorites. The app only provides easy access to dashboards on the go, though, with no editing functionality.
Looker connects to numerous applications, blocks, and custom plug-ins, which you can look up and explore on its Marketplace.
For example, you can enable HubSpot Segment integration to visualize your marketing data alongside other business data. Search the directory for an overview on “how does Segment work?”, “how much does Segment cost?”, and “how to use it along Looker and HubSpot?”
Also, Looker’s platform works with analytical datastores like BigQuery, which provides an arsenal of built-in functions to enhance your data manipulation tasks. For instance, you can CAST a string as an INT in BigQuery to parse it or make comparisons with numerical data types.
If you have dbt selected as your go-to data transformation tool, Looker will be a great next step. In fact, the tools accomplish two distinct and complimentary types of data modeling—dbt builds your data foundation, and Looker helps you navigate it. Additionally, you can deploy DBT with Snowflake into your data stack to scale up the warehouse as data size increases.
Looker has a variety of plans designed to meet specific business needs. However, the price quotes are not available on the website. You’ll have to request a custom quote, which will be calculated based on your requirements.
Based on various community posts on Slack, Reddit, and Quora, we were able to pinpoint that the entry price is around $2900/month per company. Optional add-ons include $30 for dashboard viewers, $60 for creators, and $120 for developers. Nonprofits and educators can get access to the platform for free upon request.
Looker itself is not free, but there are Looker open-source tools and repositories available on GitHub.
All this is to say that Looker is great, but it’s not the right fit for every company. There are plenty of other robust tools that can help you achieve the same, if not more.
Let’s look at 7 business intelligence platforms to add to a modern data stack.
Microsoft Power Platform, and Microsoft on the whole, include a massive number of associated platforms and applications. Therefore, Power BI gives access to functionalities extending far beyond BI and analytics. For example, thanks to Microsoft Office, Teams, Azure, and SharePoint, users can operate functions that Looker can’t.
Some of the newer advancements in the tool are AI-driven experiences, smart narratives (NLG), and anomaly detection. Another important point is that Power BI targets a non-technical audience, whereas Looker is more suitable for technical users who know LookML.
Power BI Pro costs $13.70 per user/month, and Premium costs either $27.50 per user/month or $6,858.10 per capacity/month.
Tableau offers opportunities for different data manipulations, SQL queries, forecasting, and more. However, it doesn’t surpass Looker in terms of powerful data analysis. It can still be a great tool for companies operating with large datasets, complex data views, and many third-party tools. It’s also a good fit if OLAP is irreplaceable for your analysis (which Looker cannot provide).
Tableau has fewer integrations with third-party software, and those it does offer are a bit harder to connect. The area where Tableau wins is the price: it’s open-source. Even extended functionality is relatively affordable at $15-$70/user/month.
Oracle Analytics is a platform for non-technical business analysts and consumers. Of course, users who have sufficient technical skills and knowledge can use advanced analytics capabilities. But the Oracle data platform is mostly designed for self-service, intuitive experience using natural language.
The key functionalities of the platform are data storage and prep (Oracle data lake architecture), visualization, reporting, and augmented analysis. There are, however, complaints about the quality and flexibility of graphical visualizations.
The pricing model could be improved. Right now, users need to pay unit prices for specific features, which is quite confusing. The base price is $16/user/month (Professional) and $80/user/month (Enterprise).
Metabase is an open-source BI tool. Non-technical business users can use simple no-code data questions, but natural language querying is, unfortunately, hard to navigate. The drag-and-drop data query builder is intuitive but has limited granularity.
This tool is perfect for smaller, tech-savvy startups with a low budget. If your business has engineers capable of diving deeper with SQL, setting up sophisticated data queries, and working through bottlenecks, then you’ll be able to effectively use Metabase’s data visualization capacities.
The base functionality with no customer support is free. If you want to go the paid route, there are three tiers: Starter ($85 for 5 users), Pro ($500 for 10 users), and Enterprise (starting at $15,000).
Qlik Sense is a self-service data analytics software, but it’s essentially a web-based tool. It leverages the power of artificial intelligence for a host of advanced functionalities, including smart search, data storytelling, and progressive creation. Data modeling and managed data connections are the core features.
There is a catch—businesses that are about to include Qlik in their stack should have a good technical team. You don’t want to be left alone without assistance with this tool.
The Business plan costs $30/user/month, and quotes for the Enterprise SaaS plan are available on-demand.
Sisense is AI-driven software with a scriptless interface. This business intelligence platform aims to provide APIs for customizations and analytic experiences for any type of application; it integrates with web portals, external websites, and web applications.
The main features of Sisense Fusion Analytics include ad-hoc analysis of highly voluminous data, solving queries (which doesn’t require programming), and widgets for charts, gauges, and graphs. It uses Sisense Narratives License and Boto natural language bot for English descriptions in individual widgets.
The price quotes are determined on a case-by-case basis. On the AWS marketplace, the product is sold for $35,000 per year for 1 entry server, 5 admins/designers, and 10 viewers.
QuickSight is an ML-powered solution for creating and publishing simple interactive BI dashboards. Just like with Microsoft Power BI, the most valuable feature of Amazon QuickSight is its integrations—specifically, its connectivity with other Amazon services.
From an analytics perspective, it’s better suited for self-service analytics. In other words, QuickSight’s best client is the one who needs production-ready dashboards quickly and with minimal features. The variety of visualizations is rather limited.
The pricing structure can be confusing. Authors are charged $24/month, and readers pay $0.30/session, up to $5 max/month. But there are additional charges for session capacity, questions capacity, etc.
According to Looker’s 2021 yearly report, the platform supports over 2,000 organizations of different sizes. Looker revenue is reportedly over $300 million, and the Looker stock (NASDAQ: GOOGL) was the top Big Tech stock of 2021. This level of success and popularity suggests that Looker is an optimal choice for many business users.
The most common users of Looker are mid-sized companies and enterprise-level companies that operate in the computer software industry. If your company doesn’t fit these categories, you don’t need the functionality it offers, or the price doesn’t fit your budget, there are other business intelligence platforms out there.
As you’ve just seen, there are plenty of options when it comes to choosing the right Looker alternatives for your team. The best way to learn about these solutions and how they’ll fit your organization is to contact the vendors directly. They’ll help you navigate the tool, find the right approach to your data, and make the most out of it.
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