For most people, a spreadsheet full of numbers and letters is both daunting and confusing to look at. This unstructured data has needed processing for years by specialized staff who undertake time-consuming manual procedures to extract accessible insight for use by the wider business.
With platforms like Looker, you can automate insight generation and improve access to information. You no longer need a dedicated team of analysts to create and send reports. Instead, the Looker platform can automate, extract, transform, and load (ETL) processes and provide visualized data insights that are easily understood by all employees.
With the latest version of Looker 7.0, you have access to industry-leading tools and integrations for data analytics. There are also some experimental features coming with the release of Looker 7.2 on the 20th of February 2020.
Here are some features to keep an eye on:
Looker supports a massive range of SQL database dialects, including:
Google BigQuery Legacy/Standard SQL
Microsoft Azure PostgreSQL
Microsoft Azure SQL Server 2016
This is just a small selection of the most popular database dialects you can use natively with Looker. A database dialect refers to the specific structured query language (SQL) fork used by that database system.
Looker has two separate support levels for dialects, which are ‘supported’, and ‘integration’. Looker fully supports all of the above, and they actively work to fix implementation issues as part of their platform support offering. There are other “integration” level dialects that you can connect to Looker, but they don’t offer any support for these.
Looker has been working to broaden the scope of their hosting platform support, and now supports SOC 2 Type 1 compliance as standard when deploying through the Google Cloud Platform.
A SOC 2 Type 1 certification guarantees the security, availability, and confidentiality of your datasets on a GCP hosted environment, alleviating many cybersecurity concerns for IT departments. Looker already maintains a more comprehensive SOC 2 Type 2 audit report on AWS, which covers a period of months, rather than a single point in time for SOC 2 Type 1.
Looker is continuing to expand its support, with plans for native Microsoft Azure hosting in early 2020.
Looker Actions offers a standardized form of communication between your existing collaborative work management platform, enterprise instant messaging applications, and various cloud platforms.
Collaborative Workflow and IM Integration - With Slack and Jira, you can deliver pre-compiled reports directly into your workflows to expedite cross-business communication. These can be exported directly from Looker, negating the need for conversion and manual sending.
Cross-Platform Data Delivery – Looker uses something called “cloud storage buckets” to deliver data between your various hosting platforms. Supported cloud platforms include Azure Blob Storage, Google Cloud Storage, Amazon S3, DigitalOcean Storage, and more. This makes data available across your heterogeneous network, while simultaneously decreasing bandwidth requirements by reducing the number of cross-platform network requests.
Looker provides managed data infrastructure services through its platform on AWS and GCP but still lacks Azure as an option.
For those who want to self-manage, Looker is compatible out of the box with any cloud hosting provider. You can consolidate your analytics to a single cloud platform or use the multi-cloud to take advantage of better pricing on each platform.
Trianz is a leading business intelligence and analytics consulting firm with a comprehensive understanding of the complex world of data management. We have partnered with Looker to deliver expert assessment and implementation services for their platform.
Get in touch with our BI consulting team to learn how you can remove the barriers to analytics accessibility with Trianz.
Contact Us Today
What are the Differences? Though often used interchangeably, data pipelines and ETL are two different methodologies for managing and structuring data. ETL tools are used for data extraction, transformation, and loading. Whereas data pipelines encompass the entire set of processes applied to data as it moves from one system to another. Sometimes data pipelines involve transformation, and sometimes they do not.Explore
One Unified Dashboard In the past, most enterprises would have used a legacy business management system to track business needs and understand how IT resources can fulfill these needs. The problem with these legacy systems is the manual data collection process, which introduces the risk of human error and is much slower than newer automated solutions.Explore
Intelligent automation in the workplace is becoming more relevant in the modern market. As automation technology becomes more refined and smart business models allow business owners to optimize their workflow, more and more are turning to intelligent automation for their internal and client-facing processes alike.Explore
What is a Hybrid Data Center? A hybrid data center is a computing environment that combines on-premise and cloud-based infrastructure to enable the sharing of applications and data across physical data centers and multi-cloud environments. This allows organizations to balance the security provided by on-premise infrastructure and the agility found with a public cloud environment.Explore
Leverage Your Data to Discover Hidden Potential The amount of data in the insurance industry is exploding, and the number of opportunities to leverage this data to achieve large-scale business value has exploded along with it. Rapid integration of technology makes it possible to use advanced business analytics in insurance to discover potential markets, risks, customers, and competitors, as well as plan for natural disasters.Explore
Increased Use of Data Lakes As volumes of big data continue to explode, data lakes are becoming essential for companies to leverage their data for competitive advantage. Research by Aberdeen shows that organizations that have deployed and are using data lakes outperform similar companies by nine percent in organic revenue growth.Explore