Six steps to get IoT data crunching right: The importance of organisational structure

A new whitepaper from enterprise data pipeline provider Alooma has put together six steps to more easily integrate cloud tools and IoT data sets.

Organisations have more than realised by now that a data-driven world holds the key to not only the future, but the present. Yet it takes a journey of considerable steps to realise that potential. Last year Maciej Kranz, vice president at Cisco, published an additional workbook alongside his bestselling Building the Internet of Things, which came out in 2016. Speaking to this publication in April, Kranz noted how the additional information was needed to help give organisations ‘structure…clarity, and a logical sequencing’ for building their IoT journeys.

As Alooma points out, there is no magic wand to transform huge amounts of data into meaningful concepts to accelerate business processes. Indeed, if your organisation is one of the many whose infrastructure is not cloud-optimised, then a serious architectural shift needs to take place before you even get started on the data-crunching.

“By employing common-sense planning and leveraging various data management tools, companies can get a handle on their current data, better prepare for an influx of new data, and move it all to the cloud so that it can work together and provide coherent, actionable insights,” the report notes.

The six steps advised by the company therefore focus on a holistic, considerate approach:

  • Take a data source census or inventory: It’s worth noting here that many companies will have – or at least should have – this fresh on their minds thanks to GDPR. But a survey of each team to get a comprehensive view of the information landscape is ‘critical’, the report notes
  • Identify the most relevant sources of potential new data: To best prioritise IoT data sources, specific business objectives need to be determined upfront, before identifying specific sources of new data which can be incorporated into the current information
  • Evaluate analytics tools: The report argues that IoT data may need to be crunched by a more robust system than regular business intelligence tools. “It may also be necessary for companies to replace some existing analytics tools with systems that better align with organisational goals and data governance policies,” it adds
  • Highlight new security vulnerabilities or compliance issues: As IoT pervades, attack vectors multiply – as regular readers of this publication will be more than aware
  • Devise a data integration plan: Just because IoT data doesn’t exist in a separate silo, it doesn’t mean integration of some sort can’t take place. This involves exploring cloud-based data warehouses and ETL (extract, load and transform) tools, along with other number-crunching goodness
  • Define analytics goals and objectives: The final step is where the parameters of what analysis needs to take place can be defined. “Companies should aim to create algorithms that reduce or eliminate false positives or negatives, enable analysis of both structured and unstructured data, and deliver insights in real time rather than conventional batch processing,” the report explains

“We see companies find new ways every day to use IoT, whether it’s to improve customer service, control costs, or become more efficient,” said Tasha Reasor, VP of marketing at Alooma. “But it’s difficult to put any of those mechanisms in place without the right tools and techniques that can help organisations fully access and utilise their data.”

You can read the full document here (email required).

Interested in hearing industry leaders discuss subjects like this? Attend the co-located IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

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