11 Tips For Successful Self-Service BI And Analytics - InformationWeek
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3/21/2016
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Lisa Morgan
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11 Tips For Successful Self-Service BI And Analytics

As more businesses attempt to compete with data, more people within their organizations must be able to gain insight from it. End-user requirements are changing rapidly, often at a faster pace than their employers' ability to deliver sound solutions. Here are a few ways to avoid compromising long-term benefits for short-term gains.
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Don't Forget Scalability 

What works well on a small scale isn't necessarily sustainable on a larger scale. Facebook found that out as more of its employees started using self-service analytics. In 2007, the company relied on a massive piece of infrastructure like many other companies, but ultimately scalability and quality of service became issues. So, the company became an early adopter of Hadoop.  
'When people talk about self-service analytics, they forget about the infrastructure part. [By] 2011, use-cases started sprouting, because the infrastructure and the tooling around it [were] made into a self-service platform for big data. The whole thing was very transformative,' said Ashish Thosoo, former head of big data at Facebook and CEO and founder of data-as-a-service company Qubole, in an interview.
By 2011, after a four-year effort, 30% of Facebook employees across all departments were using the self-service analytics capabilities -- including developers, advertising operations, legal, product management, user operations, and security. The overall goal was to fuel the company's rapid growth, which, at the time, included a target of 1 billion users. The company has since exceeded that goal by more than 50%.
(Image: geralt via Pixabay)

Don't Forget Scalability

What works well on a small scale isn't necessarily sustainable on a larger scale. Facebook found that out as more of its employees started using self-service analytics. In 2007, the company relied on a massive piece of infrastructure like many other companies, but ultimately scalability and quality of service became issues. So, the company became an early adopter of Hadoop.

"When people talk about self-service analytics, they forget about the infrastructure part. [By] 2011, use-cases started sprouting, because the infrastructure and the tooling around it [were] made into a self-service platform for big data. The whole thing was very transformative," said Ashish Thosoo, former head of big data at Facebook and CEO and founder of data-as-a-service company Qubole, in an interview.

By 2011, after a four-year effort, 30% of Facebook employees across all departments were using the self-service analytics capabilities -- including developers, advertising operations, legal, product management, user operations, and security. The overall goal was to fuel the company's rapid growth, which, at the time, included a target of 1 billion users. The company has since exceeded that goal by more than 50%.

(Image: geralt via Pixabay)

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Prathakbhat
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Prathakbhat,
User Rank: Apprentice
7/5/2017 | 8:32:53 AM
Infruidís Self-Service Business Intelligence tool
I would recommend you go for Infruid's Self-Service Business Intelligence tool (https://infruid.com)- Vizard.

Vizard is Infruid's patent-pending and award-winning Business Intelligence & Data Visualization tool. Vizard helps users ask questions in simple English and answers back with interactive charts.

I have personally tried their tool and the tool has a very intuitive and easy to use interface. You can use this tool without having to depend on the IT Department.
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