Few tips to implement a real-time data analytics strategy

Real-time data analytics allow data teams to perform modelling, simulations and optimisations based on a complete set of transaction data.

Real-time data analytics allows faster, more informed decisions, an improvement from conventional decision-making, usually done with stale data or in the absence of it. Real-time analytics requires a structured decision process with predefined logic, and the data must be immediately available. Acquiring the data is often the limiting factor in speedy decision-making.

With real-time insight into your market, your target audience and your competitor’s activities, you can form up-to-date strategies that reflect the changing trends of the market. For example, if a competitor lowers their prices, real-time analytics lets business analysts see the change immediately and make specific recommendations to management that realign priorities.

Read our tips below on how to implement a real-time data analytics strategy in your organisation.

Tip #1 – Understand what your company actually needs

Your team needs to answer questions like “What are the company’s goals with real-time reporting? What types of data sources matter, and what do you want to measure? What existing tools does the company already have in place? And who will utilise real-time analytical insights?”

Once you are able to gauge what your company actually requires from your real-time data analytics tool, you will be able to curate a tailor-made experience to boost your company’s optimal efficiency.

Tip #2 Triangulate sources of data and store it in a cloud

Before you can build the right data infrastructure to process and analyse all this data in real-time, you need to pinpoint precisely where you want to collect that data. Common types of data you may want to analyse in real-time include customer relationship management (CRM) data and enterprise resource management (ERP) data.

You also need to take into account data sources and the best way to manage them. Make sure to take a broad look at your company’s needs and map out all the sources of data you wish to centralise as part of your strategy for real-time analytics. Now that you know what types of data you want to analyse, you’ll need to build a data pipeline to collect and store that data in a cloud warehouse or data lake, for analysis.

Tip #3 Pick the right real-time data analytics tools

While there are a variety of analytics tools that can analyse real-time data, you want to be sure you invest in the right one. The wrong choice could leave you with more than a negative effect on your balance sheet—think low employee adoption, headaches for the engineering team and extended system downtime, if you have to replace it in the future.

It’s essential to get a good idea of what you need from your real-time analytics tool. Every company is unique, and needs will vary. We recommend evaluating internal requirements and aligning purchasing decisions with those goals.

Tip #4 Consult experts in real-time data analytics strategy

When implementing a real-time data analytics strategy, you may need to seek external assistance to curate your strategy. There are companies that would take over this tedious, complex job and will help you expertly streamline your real-time data analytics strategy.

To filter through the noise to optimise your operations and minimise downtime or hassle, a consultant could step in. More often than not, these services are provided with support teams on call 24/7 for any woes or troubles-faced.

Time to adopt real-time data analytics

Big data and real-time analytics was once a pipe dream for many enterprises. But now, businesses need real-time tools to analyse their data– and both things are more attainable than you think. Do not be afraid to venture down this road!

The modern-day business model requires quality delivered in real-time and be ever-present for changes on the horizon. To achieve this real-time performance, enterprises must now harness the power of real-time data analytics.

Gartner conducted studies on real-time analytics. Between 2017 and 2019, spending on real-time analytics grew three times faster than any other type of analytics and will be worth $22.8 billion by 2020.

Visit our website for more information on how you can leverage the power of real-time data analytics in your industry.

What’s the potential for real-time analytics in healthcare?

Back in the days of yore, there was no plausible alternate reality where the large amount of data churned out by the healthcare industry could be collected and analysed in real-time. With the advent of real-time analytics in healthcare, we see technology pushing the envelope on what we can truly achieve in this sphere.

The end goal in healthcare is to save lives, shorten hospital stays and build healthier communities around preventative care. How can real-time analytics help achieve these goals?

Centralising information to make real-time decisions

Healthcare information is disconnected and not readily accessible in a centralised, informed manner, greatly limiting the industry’s efforts to improve quality and efficiency. Real-time analytics in healthcare addresses these issues head-on by bringing disparate and siloed data from many sources into one place.

The information gained from analysing massive amounts of aggregated health data can provide actionable insight to improve operational quality and efficiency for providers and insurers alike. This increased efficiency is necessary for the healthcare industry that is rapidly transitioning from volume-based to value-based healthcare. Now more than ever, it is critical that clinicians and providers identify and address gaps in care, quality, risk, and utilisation to support improvements in clinical outcomes and financial performance.

Revolutionary real-time analytics in healthcare

In the age of prime technological advancement, we see a host of new gadgets that are revolutionising our healthcare experience. With virtual visits, real-time patient scheduling and AI that serves as the first point of care, we see convenience and efficiency take over systems that were mostly linked to being slow and ineffective.

Wearable devices, like necklaces and bracelets, are no longer purely for aesthetics, they also double as your lifesaver. These devices are useful tools in preventive care for patients because they measure vital signs to diagnose conditions like hypertension and asthma. This is only the surface of what real-time analytics in healthcare are capable of and publicly available to the masses. The research and development side of the healthcare system is testing out products that could change the very way we view healthcare.

Patient-doctor synergy achieved

Real-time analytics in healthcare has the potential to greatly impact the patient-doctor synergy. Smart devices encourage patients to be more involved in their own treatment process, empowering them to take their health into their own hands.

Through remote health monitoring, patients will have real-time visibility into their vital signs, such as blood pressure and heart rate. Not only will this information give patients insight into how their habits contribute to their health and motivate them to follow the treatment, it also allows nurses or medical officers to receive alerts should a patient’s condition change or reminders need to be scheduled.

With real-time analytics, hospitals can have a 360-degree view of the patient. Using this data, the healthcare industry can deliver proactive care, improving health outcomes, reducing hospital readmissions and improving all-round efficiency.

Real-time analytics in healthcare allows clinicians to go deeper and broader in medical services. But most clinicians are hampered in their inability to access and analyse said data. Access to patient history data is often difficult to come by, and even if the data comes through, analysing and incorporating it meaningfully into diagnosis is a challenge. However, real-time analytics in healthcare can resolve this problem.

Real-time analytics can combine insight from historical information with current data, making it easier to conduct a deeper and more comprehensive treatment than before. Naturally, both medical providers and patients benefit from the use of data analytics.

Moving forward

Healthcare thrives on real-time information and as the industry is further empowered by technology, a growing number of healthcare management systems are leveraging real-time analytics to give healthcare providers every single advantage possible. Superior analytics platforms enable predictive analytics of data in motion, allowing healthcare providers to capture and analyse data – all the time, just in time.

Among the benefits of big data in healthcare is the possibility to improve the quality of medical services, track financial performance and detect fraud while freeing doctors from routine work. The newfound freedom gives doctors more time to do what they have to do – help people maintain their health and anticipate unforeseen health issues in time.

Visit our website for more information on real-time analytics in healthcare.

Is streaming analytics the asset you need right now?

The idea of streaming analytics or real-time analytics isn’t new, but the idea holds more weight than ever before with what’s going on in the world right now. Organisations need technology that empowers them to operate with greater speed and efficiency, and the ability to analyse data in real-time can do that. In this blog post, I explain what streaming analytics is and how it can help organisations during these trying times.

What is streaming analytics?

As the name implies, streaming analytics refers to analytics capabilities that can capture and analyse data as it is being streamed into the system. Unlike conventional analytics systems, real-time analytics does not require data to be stored and cleaned for analysis because the system is analysing data through continuous querying.

There are two types of real-time analytics: On-demand real-time analytics and continuous real-time analytics. The former focuses on a reactive analysis approach, while the latter takes a more proactive approach to analysis.

With real-time analytics, the system processes a query from a user to give results immediately. Meanwhile, continuous real-time analytics regularly updates the system with alerts in real-time without user input. Depending on their needs, some systems are better suited for some organisations over others.

Why is streaming or real-time analytics helpful to organisations?

Streaming analytics is a vital asset for any business because it can capture and process data as it is coming through the system. This allows the organisation to create contextually relevant reports based on the latest data. With this system, businesses can create and finalise their findings within minutes, allowing them to act faster and be more proactive.

Real-time analytics can be especially beneficial for organisations during these trying times. For example, if you want to create business plans for the future, you would want to know the latest information on the COVID-19 virus.

Streaming analytics allows you to integrate the data from a relevant database, as it is being updated, to create reports based on the latest data. Alternatively, the analytics system can also update an external database, if necessary.

Analytics platforms with real-time capability allow organisations to create their strategies around timely relevant data, which improves the quality of decision-making and gives them more accurate options. Furthermore, it improves the overall analysis process because it removes a redundant step, allowing businesses to generate insights at a faster, more efficient rate.

With streaming analytics, organisations are better equipped to handle the future. Organisations will now find it much easier to anticipate in terms of what might happen in the long run and plan for it. This is because real-time analytics reflects the latest developments in a situation, something which is invaluable when we need to know how the pandemic will hurt our fortunes and lives.

Data visualisation is another huge benefit of streaming analytics. Visualisation is vital for the processing of information – let’s face it, it’s much easier to analyse data when it’s presented as graphs and charts instead of lines of numbers. With real-time analytics, organisations are in a better position to analyse their KPIs with in-depth detail.

Organisations can breakdown and examine every granular view of their performance. This includes costs, sales and even information. Given current circumstances, the ability to analyse every aspect of operations could pave the way for innovative solutions to the massive problem that is the COVID-19 pandemic.

Under normal circumstances, streaming analytics allows organisations to better understand their customers and buying preferences. Given the pandemic, customer behaviour would have changed significantly, but how are they spending their extra time? How are they obtaining their necessities? Are they still in the market for goods and services? Are they out of a job?

Streaming analytics makes it easier for any organisation to answer these questions. Organisations directly involved in combating the virus would want to know the latest on people’s movements, the direction the virus is spreading, along with hundreds of other variables. Thanks to analytics, organisations now have that capability.

Investing in the right platform

Public and private organisations across different industries are having a hard time navigating the pandemic. During this time, every organisation is going to need every tool that can help them stay afloat.

Streaming analytics allows organisations to be more responsive, agile and smarter in their decision-making process.