Live Streaming Analytics

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There are many situations why data streaming, or real-time data analytics, is becoming essential to its future growth. However, one of the most obvious choices is speed and reliability.

In the face of the twist of market shifts, data and analytics leaders require an ever-increasing acceleration and scale of analysis, in terms of processing and usage, to accelerate innovation and forge new paths to a post-Covid-19 world.

As a business, the businessman always wants to know more about the customers and find ways to be more efficient. The real-time analytics offers you that chance – and there seems to be no limit to where it can make a meaningful impact.

Perhaps it is no surprise, then, that by 2022 most business systems will feature real-time data capabilities. 

Business intelligence is demanding it. In the year 2021 and the prospect of a post-pandemic world, we will see an appetite for technologies that can combine to enable genuinely personalized, live, informed decisions to be made.

Real-time data flows can revolutionize the way organizations learn and interact with customers. When we emerge from this pandemic, this sort of detail will be essential for businesses to navigate some turbulent waters ahead.

The future of customer experience is now found. Customers will be a little complicated than before when it comes to dealing with their money. Simultaneously, 90% would abandon companies after just two to five poor customer service examples before moving to compete for brands.

Real-time data analytics is already impacting decision-making across industries, cutting down decision-making time, and making those decisions more accurate and lasting.

An excellent example of this is in Zurich, one of the world’s smartest cities. Thanks to living streaming data analytics through the Vianova mobility data platform, the city has increased transport policy response times. The result has created two new dedicated cycle lanes and a dedicated parking infrastructure for e-mobility, developing multi-modal journeys, the quality of transport services, and reducing waiting times.

In transport, changes in people flow are caused by post-pandemic trends, including working from home and avoiding mass transit modes. Higher parcel delivery volumes are highlighting the requirement for real-time analytics at the local authority level.

This is particularly necessary for having the growth of micro-mobility substitutes such as e-scooter services. In many cases, multiple private operators are involved, so live data sharing helps them work with local authorities to ensure their services are safe, effective deployment. If we want smart cities to be anything more than eloquence, they will need to be built on the foundations of data sharing and real-time analytics.

What is clear is that real-time analytics will touch almost every industry at some point over the next few years. This includes the UK government’s drive towards making the tax system digital by 2022.

Tax data analytics provide insight into existing and live tax data using natural language processing (NLP), which interrogates the data at the source, such as directly from ERP [enterprise resource planning] or accounting software,

This provides real advantages. For instance, with regards to compliance, it allows you to evidence claims assessments to provide proof of entitlement so that you can quickly respond to any challenges from HMRC [HM Revenue and Customs]. You can also ensure you maximize tax relief, track appropriate tax rates across different entities, and keep on top of deadlines.

Smart data means smart decisions. Many businesses have understood that they need to capture data, increasingly in real-time, to understand better how their business is operating and make it easier to adapt.

However, understanding better what is the right data to retain and leverage is a challenge. Capturing and retaining ”everything” and putting it into cheap object stores creates swamps that become increasingly difficult to draw value from, let alone leverage in an adaptive manner. So being smart about what to collect and how it has been maintained and used is crucial.

Legacy software, combined with vast unstructured data, represents the organization’s most significant challenge using real-time decision-making data. Most companies do not even know terabytes (and often petabytes) of unstructured data floating around in their systems.

This is worrying if leaders, perhaps under pressure to deliver data-driven trends and analysis, are forging ahead using tools and platforms not entirely built for the job. It is a common problem because not everyone has the budget to rip and replace systems. It is almost unavoidable that, in some situations, legacy IT and data siloes will get in the way of progress.

Since 90% of the world’s data is now unstructured, we need more advances in analyzing and visualizing unstructured data.

That makes sense. Predictions in its Top 10 trends for data and analytics in 2020 paper, the traditional data dashboard will decline in use. Dynamic data stories with more automated and consumer-focused experiences will replace visual, point-and-click authoring, and exploration.

The shift to in-context data stories means the most relevant insights will stream to each user based on their context, role, or use. They are leveraging augmented analytics, NLP, and streaming anomaly detection, and collaboration.

Indeed, artificial intelligence (AI) techniques such as machine learning (ML), optimization, and NLP are needed to manage data infrastructures and deliver insights and even predictions. Investment in automated data platforms will only increase, leading to further changes in how data is streamed and managed in the future. The challenge now is to use the data companies better and improve speeds to enable better streaming.

Only 11% of retail, consumer packaged goods, and manufacturing organizations have access to data that is less than an hour old, meaning there is a significant delay in their ability to use this data to make timely and informed decisions.

There are considerable benefits to streaming live data, but for the moment, at least, this remains a fragmented and complex industry, but one that is on the leading edge of change. Any business that gets it right now will be able to face the post-pandemic future with a certain degree of well-informed optimism.