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New Year’s resolutions for businesses leveraging Big Data in 2019

New Year’s resolutions for businesses leveraging Big Data in 2019

CloudInsightsSoftwareTop Stories

Kunal Agarwal, CEO of Unravel Data, talks to us about how businesses can best leverage Big Data this year to compete and adapt within the ever transforming tech market.

January marks the beginning of a New Year and it is around this time that organisations reflect on the year just passed as well as look forward to what the new one has in store. Every year should bring a climate of change and renewal, but in 2019 this will be increasingly important as major businesses in every sector increasingly seek to harness the power of data to transform their strategy and stay competitive.

In the same way that people make personal resolutions and commitments to doing better in the New Year, organisations should do the same to become their best selves. Below are three key areas that organisations looking to leverage Big Data for better business outcomes should consider:

Adopt new cloud services to handle the Big Data stack

The continued migration to cloud services by enterprises everywhere means that Big Data systems become increasingly critical; cloud technologies naturally embrace and encourage innovation through allowing IT teams to spin up and tear down workloads with great flexibility and agile experimentation.

The industry is racing towards new ways of using cloud services to enable a more agile Big Data stack and indeed, hybrid cloud models continue to emerge that consider internal and external service delivery so that enterprises receive a really customised, cost-efficient operation.

AIOps, the convergence of Artificial Intelligence (AI) with ITOps, can provide predictive operational tuning automation in which infrastructure intelligently adapts based on historical data and will continue to do so based on the present and future application patterns.

If we accept this premise, then we’d expect to see AIOps melding with DevOps as a top priority for the enterprise as data becomes central to the SDLC process and IT teams would do well to prioritise incorporating these concepts into their roadmap the success of modern data applications.

Address the skills gap

It’s a widely acknowledged truth that the talent gap within the DevOps and Big Data space is becoming quite an enterprise challenge. In a study conducted with Sapio Research, we found that 36% of enterprise business and IT chiefs cited talent scarcity as a huge pain point. The skills shortage is no new phenomena in this area of IT, nor the wider tech space. With Big Data being a relatively new IT concept, it takes time to educate, train and empower staff to fully embrace it.

A greater need for balance

In order to achieve a fully holistic approach to delivery underpinned by Big Data insights, there needs to be a balance of innovation and control, testing and production, efficiency and effectiveness. Finding that balance will require enterprises to take some calculated risks, but this can be done without live production suffering as automation and intelligence supports the DevOps team in their task of making the magic happen.

Enterprises must find a way to stitch the fabric of the data stack together to get fast, usable insights and recommendations into the operations powering their business intelligence, customer service and forecasting applications. Efficiency and effectiveness must be tightly controlled or the whole stack will rapidly spiral out of control in 2019.

Automate everything

Where possible, it is a given that organisations should look to implement automation in order to streamline processes, reduced operational overhead and maximise strategic output. Any organisation, regardless of size, can employ Machine Learning (ML) in order to help utilise Big Data to achieve higher levels of performance through automated actions that deliver repeatable and transparent decisions that do not require human intervention.

Making it happen

By applying an end-to-end tool to manage applications for performance and utilisation, organisations can leverage the cloud with ease with full confidence that data is being utilised effectively. By automatically providing specific recommendations for solving performance issues, such technology can help alleviate the skills gap by reducing the need for human intervention.

Finally, by helping businesses gather information in order to create more compelling customer experiences, gain deeper market insights and drive more efficient and effective use of resources, application performance software can allow IT teams to focus their time and efforts across objectives by taking care of the maintenance layer and allowing for more pioneering initiatives.

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