The amounts of data available to us are growing at an exponential rate, due to the prevalence of the internet in modern life. Businesses have an increasing need to categorize the data that they process and format it in ways that are accessible to both staff and customers alike. Big data analytics firms like Looker are pioneering the way forward for accessible big data analytics by providing easily scalable access to reliable corporate datasets.
What is Looker and what does it do?
- Simplifying Data Lookup - The Looker service was created to expedite the process of finding data across a business. It aims to replicate the role of business intelligence firms by compiling and sorting corporate data while offering insights into useful data patterns.
- The Power of SQL, without the code - Looker allows you to harness the power of the Structured Query Language (SQL) to create insightful groups of information without using technical methods of extraction.
Traditionally, big data analytics firms would require technical IT staff with knowledge of SQL database querying. This lack of technical expertise significantly reduced the accessibility of databases, alongside creating a bottleneck for information needed to make critical business decisions. Instead of directly using the SQL language, Looker allows the user to communicate with a database through a graphical user interface, called LookML
The biggest benefits of Looker
- Increased Productivity - Looker increases productivity by extending the capabilities of business analysts to every member of staff in the company. It is possible to access the database and make a query on any device that supports the HTML5 web standard, which is virtually any modern device running Windows, MacOS, iOS, or Android. It essentially negates the need for traditional business analysts, which expedites the querying process.
- Visually Pleasing Analytics Visualizations - A considerable benefit of the Looker platform is its ability to create user-friendly visualizations of information in your database. The friendly user dashboard is available which stores datasets that have previously been used for easy access at a later date.
- Collaborative Team Functionality – Looker also allows you to share visualizations you’ve created with colleagues in your company. These visualizations can be viewed using any web browser on devices that support HTML5, in contrast to software from other business intelligence firms like Qlik and Tableau. You have your own space to save reports, alongside groups where you can share visualizations of your most important analytics with colleagues.
How does Looker improve productivity?
Many businesses have struggled with the scalability of their database querying. Large companies with multiple offices across the world need access to informative data to allow them to make the right business decisions.
Traditional SQL querying is something that would be completed by business analysts within your corporate IT team. This querying is a slow process as they have to manually work through query requests daily from a variety of departments. Those that had submitted a query for review would have to wait for extended periods to find out the information they needed. This wait ends up delaying business processes and also significantly reduces the agility of the business when faced with on the spot decisions. These delays in big data analytics consulting across your business can dramatically reduce productivity.
Alongside Looker’s improved availability across a wide range of devices, it is also more accessible to the company’s general workforce, especially for those with that struggle with technology. Business analysts would need to have knowledge of the Structured Query Language to interface with the database and perform any big data analytics. Looker uses an abstraction layer called LookML, which creates re-usable business metrics that are easy to understand and remain flexible with changes to your database. The reusability of LookML is one of the most significant benefits of Looker, as business intelligence analysts would have to tailor their SQL code to each query, making for an inefficient method of extracting data.