From business need to roll-out: A summary of our series
- Big Data Section (article 6 of 6) -
In our previous articles, we presented the main factors you should consider when devising your big data strategy. Here’s a summary to wrap up the series.
First, any big data initiative must be strategic and driven by your business needs.
Customer or product information isn’t just found in the company’s operational systems. It can also come from social media, digital communications, the Internet, smartphones, connected devices, etc. Since business strategies increasingly rely on the exploitation of this data, companies need to collect it so that they can derive new knowledge and deeper understandings that can help them respond to specific concerns.
Big data is no different from other emerging technologies that companies have adopted and integrated over the years. Introducing big data has multi-dimensional impacts on the organization, its processes and its infrastructure. It must therefore be guided by the same management practices already in place within most organizations.
Big data is shaking up current practices and data management knowledge areas—especially architecture, modelling and design, storage and operations, security, integration, quality, data warehousing and business intelligence systems.
Unlike traditional data management, big data is all about massive volumes of data, which is generally sourced externally. Its purpose is to derive new knowledge or ideas that are useful to the company and otherwise impossible to detect using traditional data warehouse approaches.
In the context of big data, information can rush in and massive volumes can accumulate in a very short period of time. For companies, high velocity requires highly elastic processing capacities for data that comes from various sources in different formats and available with corresponding storage capacities. The wide range of incoming data makes it challenging for companies to integrate, transform, process and store it.
In order to handle this varied information, big data environments have to be distributed, scalable and fault-tolerant. This is a departure from most companies’ established practices. The Hadoop distributions and solutions available on the market take the complexity of big data into account, but their stability and portability remains an important issue for IT operations.
Because of the complexity and flexibility of the material resources that make up infrastructure and the rapid progression in big data tools, it makes sense to externalize environments to cloud computing. That way, suppliers assume the technological risks. But does this apply to all companies?
Before you choose the best solution for your needs, you need to consider the various options, assess all associated risks and select the scenario that involves the lowest risk while allowing you to reach your goals at the lowest possible cost.
NOVIPRO offers a big data maturity model that, when combined with a complete risk analysis, can help you find the answer with confidence and eliminate any negative consequences that could jeopardize your big data strategy.
The big data transformation according to NOVIPRO
For more than five years now, NOVIPRO has been investing in the development and evolution of its IT transformation methodology to help companies switch to new technologies such as the cloud, big data and the Internet of things.
This methodology is based on a 360-degree approach in which the IT departments, their work processes and the technology in place all revolve around the company’s business needs, which are at the heart of the analysis.
The methodology proposes progressing through various maturity levels to upgrade your IT via cycles of continuous improvement. Each cycle enhances the organization’s agility by simplifying structures and work processes, and optimizes technologies and the way they’re used.
The methodology is totally agnostic or supplier-independent, as it’s based on reference frameworks that are known, independent and reputable.
This concludes our exploration of big data. We hope this series helped you better understand how it works. If you need assistance, NOVIPRO can help you run diagnostics and make the right decisions for the needs of your business.
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