Big Data time is money
Companies that need days or weeks to use the data available to them are facing increasing pressure. The saying “time is money” is particularly fitting in such cases and can be extended further by today’s standards: “The right data at the right time is money.” It’s not a marketing slogan but a fact that big data and the cloud are a perfect team – a match made in heaven.
Pressure on companies is growing. There is not much time from the request to the implementation of new business ideas or adaptations. Likewise, the buzzword “time-to-insight” has long since become a key performance indicator (KPI).
Companies today have to be flexible in responding to new business requirements, and the launch of new production applications cannot be impaired by an unpredictable technology or be outside of budget because new infrastructure is necessary. Special care must also be taken to protect the data used. This applies to client data, as well as corporate data.
It is essential to provide secure and direct access – preferably in real time – to the data already available in a company and to evaluate this data according to the rules of data protection and privacy.
Nevertheless, there are still companies that develop and upgrade their infrastructure and applications on their own. The argument for this approach is the company wants to keep full control of the process and protect its data and infrastructure. If you have enough time and money, go right ahead. However, speaking from experience, dedicated solutions for every scenario for an entire company are neither secure nor flexible.
Not just a pithy saying but a fact
There are simple but also clear reasons why big data and the cloud are such a good fit for each other – and make dedicated special solutions obsolete.
A combined big data cloud solution offers clients the agility to respond to the exploding volumes of data and rapidly changing business requirements. Companies can start with a pilot and integrate it on a scalable basis in their production network. Hadoop as a service, that is, Hadoop from the cloud is a perfect example. Clients do not need to have a pre-existing hardware (cluster), only data. The data rates and data analysis tool can be expanded from the PC.
Dynamic cloud solution beats dedicated in-house implementation
No CIO wants to admit after implementing a dedicated in-house solution that this model is more capital-intensive than a dynamic cloud solution. It pays therefore to consult with experts in advance. We recommend choosing a provider that offers more than just big data consulting. Decision-makers should expect more than pure consulting and should look, specifically, for providers that offer solutions and tools tailored to fit the client’s needs, such as a readiness assessment or discovery workshop. Everything else is theoretical consulting and only covers part of the solution.
Big data from the cloud or do-it-yourself?
Companies now dealing with the big data question should ask their suppliers to provide a proposal for an end-to-end solution, from planning to implementation. And they should make sure the supplier has the experience required.