A new data analytics trend might be daunting, but data analytics is integral to any business’s growth and equally important is keeping up with changes in this area. Today’s trends indicate that companies are changing how they analyse their data. Gartner reports that 37% of businesses employ artificial intelligence (AI) for their business operations, while PwC Global states that AI is expected to contribute 15.7 trillion dollars to the economy worldwide by 2030. But why is this noteworthy?
The business world is increasingly reliant on systems driven by machine learning and artificial intelligence to reliably collect and analyse information, pick up patterns, and gather actionable insights. Any company that wants to stay ahead of the competition needs to keep up, continuously improving its processes – unsurprisingly, are often underpinned by data analytics, thus allowing businesses to fast-track their operations.
You must keep up with data analytics trends to ensure that your processes are equipped to run smoothly in 2022, 2023, and far into the digital future.
What Is Data Analytics?
What data analytics is, is a science geared towards helping individuals and organisations run their operations more effectively and efficiently. Using various tools and techniques, a set of raw numbers (data) can be transformed into informative, actionable insights that drive better decision-making. Once datasets are collected, they are then ‘cleansed’ so that any incomplete, incorrect, or duplicated data can be removed.
This “data cleansing” delivers more accurate results, providing your business with reliable information and offering insight into their strengths and weaknesses and potential solutions for their unique challenges.
The Benefits of Data Analytics
Did you know that when a company uses big data to improve their business operations, it can increase its operating margin by more than 60%? This is just one potential benefit for companies that harness data analytics in an effective way. What data analytics offers a business are:
- Better Decision-Making. Data analytics can boost your business’s performance, enhance business processes, and lead to quicker and more accurate decision-making.
Ultimately, data is a critical component in the foundation of your decision-making. Thus, it needs to be accurate. Otherwise, you are making decisions blindly or without considering the data at all, thus exposing your business to risks and potential disaster – something you might not be able to recover from.
- Improve Customer Experience. By investigating customer preferences through their online interactions with your brand (such as website visits, social media traffic, engagement, and followers), your company can tailor and personalise the interaction and experience to better suit the consumer. The better you understand your customer, the more targeted and effective marketing strategies can be. This, in turn, improves overall operational efficiency.
All of this comes down to data analytics, which provides these insights to help you improve your customers’ experiences.
- Prepare For The Unexpected. Data analytics gives companies the information they need to anticipate change and navigate uncertainty, aiding risk identification and management. Risks can be internal, such as inadequate management and lack of funding, or external, such as politics, regulations, and macroeconomic conditions.
An organisation can adjust its internal processes and adapt to changes in the surrounding economic environment by employing effective data analysis processes and focusing on critical areas timeously. Data analytics makes it possible to weather the latest storm, enabling your team to focus on their core tasks within your business instead of continuously managing problems.
The Problem With Historical Data and Legacy Systems For Data Analytics
The problem with legacy systems is that they are inflexible and do not integrate seamlessly with other technologies and processes. This causes a disconnect between departments and makes efficiency unattainable and communication a nightmare. Outdated systems can also impact business productivity; up to 45% of employees complain that outdated versions impede their productivity. In turn, this can lead to poor customer service, which ultimately damages profits.
As opposed to AI, which utilises real-time data, legacy systems do not have the capability to back up data timeously and keep statistical results updated. What data analytics should offer are actionable insights, but if that data is pulled from outdated technology, it may not be accurate. Therefore, any decisions based on these datasets would be misinformed.
The best way for a company to combat these pitfalls and guarantee the accuracy and relevancy of its data analytics is to keep all systems and technology up to date. Businesses should monitor the latest data analytics trends to ensure they’re using the best systems and technology to support their data analytics.
Data Analytics Trend #1: Composable Analytics
The first data analytics trend we are highlighting is composable analytics. Composable analytics allows you to assemble and reconstruct data products and data processing pipelines more flexibly, adaptably, or modularly. Businesses can gain considerably more control over the codebase by using a modular framework rather than a monolithic one.
- A monolithic framework is more outdated, composed of a single program using a single platform. Monolithic architecture is simple to develop, test, deploy and scale; however, updates and maintenance can be difficult. A single bug in any module can potentially bring the whole process crashing down.
- By comparison, modular frameworks run many on small, independent scripts. The genius behind this system is that it combines data and operations from multiple sources, making collaboration easier. Modular division of scrips means that maintenance and scalability become easier. With this kind of flexible, software-driven analytics process, tracking and monitoring big data becomes simpler.
Composable analytics could increase the longevity of a business. It’s a data analytics trend that’s here to stay.
Data Analytics Trend #2: AI Integration
Artificial intelligence in data analytics is a rapidly advancing trend, gaining significant influence in industries from transport to healthcare. With AI-integrated processes, businesses can utilise an automated system, which is more reliable than a manual one.
The benefits of this AI-integrated data analytics trend include the following:
- Adaptability and flexibility.
- Reliable privacy protection.
- Automated systems that respond quickly to change.
- Relevant and accurate end results.
AI technology can be applied to diagnostic, predictive, and prescriptive data analytics. Having an automated system determine why something has happened and then using that data to predict what is most likely to happen moving forward is a huge benefit to organisations. They can then make big decisions more confidently and with less fear of human error, meaning their operations and ROI will likely improve significantly.
Data Analytics Trend #3: Engineered Decision Intelligence
Engineered Decision Intelligence (DI) uses AI and other technology to enable better decision-making and address issues and needs within a business. Data is collected and modelled with machine learning to accurately determine certain outcomes. DI and machine learning are combined to help organisations make decisions based on the trends identified in data sets.
Combining this technology with composable analytics and common data fabric can help businesses take action faster and more confidently. They can therefore keep up with internal and external factors in their industry and ensure business stability.
Data Analytics Trend #4: Advancements in Cloud Computing and Machine Learning
A key data analytics trend of 2023 is the increasing use of hybrid cloud services and cloud computation. Cloud computation uses a network of remote servers hosted on the internet for managing and storing data instead of a personal computer or local server.
Public cloud services are less expensive, but they’re also less secure. Private clouds have tighter security but at a greater financial cost. The great thing about hybrid cloud clouds is that they strike a balance between cost and security while providing a network for applications and components to operate together.
The popularity of hybrid cloud computing is growing expeditiously. It’s clear to see why when you consider the benefits:
- Assists with dynamic workloads.
- Easily scalable.
- Interactive functionality.
- Allows for high-priority and low-priority workloads to be kept separate.
- Processes big data.
- Lowers operational costs.
- Offers flexibility for future business needs.
Processing massive amounts of data is overwhelming. Edge computing, also known as quantum computing, is changing how data is stored, processed, transported and analysed to make the entire process easier. Edge computing is capturing, processing and analysing data closer to where it is created rather than using a centralised data-processing warehouse. This means that data is stored at the ‘edge’ of a network instead of at the central server or data centre.
The benefits of edge computing include the following:
- Boosts business performance.
- Provides tighter security and data privacy.
- Reduces operational costs.
- Meets compliance requirements.
- Supports artificial intelligence and machine learning applications.
In addition, edge computing uses significantly less bandwidth and can solve a problem in less than 200 seconds. For context, this processing speed is far superior to traditional computing methods. With the ability to analyse enormous amounts of data at an admirably high speed, this data analytics trend is a game changer.
By replacing archaic processes and legacy systems with quantum computing solutions, businesses can improve their employee and customer experience, positively impacting their profitability.
Embrace Data Analytics Trends With solverASSIST’s Innovative Technology
Rapid technological advancements have resulted in a massive shift in data analytics trends. No organisation wants to fall behind its competitors, especially when the benefits of employing a modern approach to data analytics are so obvious, yet embracing these trends and improving your data analytics can be daunting.
At solverASSIST, we provide comprehensive support for your data analytics processing, cleansing, mining, and much more. In addition, we build artificial intelligence and machine learning models that empower you to get the most out of your data.
We understand business. We also understand data and technology. We aim to give you the intelligence you need to move your business confidently into the future. Let us help you keep up with data analytics trends.
Contact us, and let’s discuss your needs.