The Top 5 Data and Analytics Trends In?2023

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------------------------------------------------------------------------------------------------------------Data analytics is a term that’s come to be used to describe the science of analyzing raw data to make conclusions about that information. Used correctly, insights derived should help a business optimize its performance, perform more efficiently, maximize profit, reduce risk, or make better strategically-guided decisions.

The history of data analytics is filled with promises about empowering entire organizations to be more data-driven. Capabilities like data visualization, self-service and cloud modernization have arisen in recent times, and yet insights from business data continue to be tantalizingly out of reach for most people. Data is typically stuck in silos and in static, hard-to-use dashboards, while data is locked away from access by IT departments and insights gleaned by analysts never move into operational processes.

Moving to a data-driven business model — where decisions are made based on hard data, rather than a “gut feeling” is core to the wave of digital transformation sweeping through every industry in 2023 and beyond. It helps us to react with certainty in an uncertain world — especially when wars and pandemics upset the status quo.

But the world of data and analytics never stands still. New technologies are constantly emerging that offer faster and more accurate access to insights. New trends emerge, bringing us new thinking on the best ways to put it to work across business and society at large. So, here’s my rundown of what I believe are the most important trends that will affect the way we use data and analytics to drive business growth in 2023.

Artificial Intelligence

Artificial intelligence (AI) is perhaps the one technology trend that will have the biggest impact on how we live, work and do business in the future. Its effect on business analytics will be to enable more accurate predictions, reduce the amount of time we spend on mundane and repetitive work like data gathering and data cleansing, and to empower workforces to act on data-driven insights, whatever their role and level of technical expertise.

AI allows businesses to analyze data and draw out insights far more quickly than would ever be possible manually, using software algorithms that get better and better at their job as they are fed more data. This is the basic principle of machine learning (ML), which is the form of AI used in business today.

Don’t think that AI and ML technologies are limited to just boring and repetitive tasks either. They can also perform a range of tasks which require human intelligence and input. This includes tasks such as recognizing speech and images, solving problems, making decisions, and adapting to new situations. Practical examples include helping to identify patterns of fraudulent credit card transactions, or false insurance claims for example. They are also deployed in helping determine the risk profile of a customer looking to secure finance, or get an insurance quote. These financial based models are fed a vast amount of data points of structured and unstructured data in an attempt to generate an accurate decision or price based upon the perceived risk.

A great example of a technology which helps enable this is Dataiku, an intuitive, business-friendly AI tool which seeks to enable all types of users (both technical and non-technical) the ability to create their own pipelines and models. If you’re interested in finding out more about Dataiku then check out my video on it?here .

Data Democratization

Data democratization — the fancy name for putting the tools and data into the hands of people who need it most. This trend doesn’t look to discriminate between data consumers’ background or experience, meaning we’re not talking about data engineers and data scientists exclusively any longer. The goal is to empower everyone with the information they need to make informed decisions and improve overall performance. This includes business users, such as managers, marketers, and salespeople, as well as technical users, such as data scientists and engineers.

This means that education and enablement are key ingredients here, ensuring a solid level of data literacy is crucial to ensure the success of a strategy which looks to break down data silos and democratize data across an organization.

In 2023, businesses will understand that data is the key to forming deeper relationships with customers, developing better products and services, and optimizing their internal operations to reduce costs and waste. However, it’s becoming increasingly clear that this won’t fully happen until the power to act on data-driven insights is available to frontline, shop floor, and non-technical staff, as well as functions such as marketing and finance. After all, no business user wants to raise a ticket with data teams and wait months until their request finally reaches the top of the pile! The business doesn’t stop, which typically means by the time a request is fulfilled by a traditional IT model there’s already a bunch of additional requests from the same business unit in the backlog waiting to be addressed.

Research by McKinsey has found that companies that make data accessible to their entire workforce are 40 times more likely to say analytics has a positive impact on revenue. The bottom line here is that you cannot ignore data democratization and the insatiable appetite the business has for data will continue to increase exponentially.

Cloud modernization (Data-as-a-Service)

I’ve grouped cloud and data as a service together as the cloud is the enabling platform for data-as-a-service technology to work. Data-as-a-Service or DaaS is a cloud-based delivery model in which data is provided to users over the internet. This data is typically sourced from various internal and external sources, and is processed and organized into a usable format. This means that companies can access data sources that have been collected and curated by third parties via cloud services on a pay-as-you-go or subscription-based billing model.

This reduces the need for companies to worry about the technicalities of data management, such as storage, security, and maintenance which lowers the barrier to entry for those smaller, start up companies. This levels the playing field dramatically, where for the first time, small companies have access to the same capabilities as the well established global organizations. Furthermore the new players don’t have any legacy technology to worry about!

A great example of this is the Snowflake data cloud, which leverages the Snowflake marketplace to seamlessly share datasets without the need to physically copy data from one place to another. It allows organizations to share and consume up-to-date datasets which creates opportunities to monetize existing data sets, or augment internal data with externally available data to generate new insight or develop better products for example. If you’d like to learn more about monetizing your data assets then check out my video?here .

Cloud based technologies play a big part in the democratization of data mentioned previously, as it allows businesses to work with data without needing to establish and maintain expensive and specialized data science operations. In 2023, it’s estimated that the value of the market for these services will?grow to $10.7 billion .

Real-Time Data

When using data to make operational decisions or manage risk proactively, it’s often better to know what’s going on right now — rather than yesterday, last week, or last month. This is why real-time data is increasingly becoming the most valuable source of information for businesses. Real-time data is used in various applications, such as financial transactions, logistics, social media, and IoT devices, where speed and accuracy are critical.

Working with real-time data often requires a more sophisticated data and analytics infrastructure, which means more complexity and expense. However, the benefit here is that we’re able to act on information as it happens. This could involve analyzing clickstream data from visitors to our website to work out what offers and promotions to put in front of them, or in financial services, it could mean?monitoring transactions ?as they take place around the world to watch out for warning signs of fraud. Another example is monitoring the prices customers are quoted for insurance policies soon after making important decisioning changes. Picking up an error early — in what is a complex process — could be the difference between saving or losing millions of dollars.

Social media sites like Facebook analyze?hundreds of gigabytes of data per second ?for a range of use cases, including serving up advertising and preventing the spread of fake news. And don’t think this technology is in its infancy either — in 2008,?Dominos Pizza ?released its pizza tracker so that fans could monitor in real time if their pizza was in the oven or out for delivery. By 2019, 65% of Dominos’ sales came through digital channels including home devices and emoji texts, reimagining the brand for the digital era.

As more organizations look to data to provide them with a competitive edge, those with the most advanced data strategies will increasingly look towards the most valuable and up-to-date data. It’s the fact that real-time data and analytics technologies have matured enough over the past few years to break into the mainstream which is why it features as part of my top 5 trends for 2023.

If you’d like to learn more about how Snowflake allows you to work with real-time streaming event data check out my video?here .

Data Governance and Regulation

Data governance will also be big news in 2023 as more governments introduce laws designed to regulate the use of personal and other types of data. Data governance refers to the policies, processes, and practices that govern the management, usage, and protection of an organization’s data. This includes defining roles and responsibilities, setting data quality standards, implementing security measures, and ensuring compliance with relevant laws and regulations. The goal of data governance is to ensure that data is accurate, consistent, secure, and accessible, and that it is used in an ethical and compliant manner.

GDPR wasn’t the beginning and it certainly won’t be the end. Strict data privacy legislation is appearing in more and more economies across the globe, meaning the list of “GDPR-free” havens is growing shorter by the day. Canada, China, India and many more countries are likely to follow suit and introduce legislation protecting the data of their citizens. In fact, analysts at Gartner have?predicted ?that by 2023, 65% of the world’s population will be covered by regulations similar to GDPR.

This regulation coupled with recent high profile data breaches at?Optus ?and?Medibank ?means that governance will be an important task for businesses in the coming 12 months, wherever they are located in the world, as they move to ensure that their internal data processing and handling procedures are adequately documented and understood.

For many businesses, this will mean firstly understanding exactly what information they have, where it is, what it’s used for and how it is collected. While this may sound like a lot of additional work, in the long term, the idea is that all parties will benefit as consumers will be more willing to trust organizations with their data if they are sure it will be well looked after. Those organizations will then be able to use this data to develop products and services that align more closely with what we need at prices we can afford.

If you would like to know more about how to technically manage your sensitive data within your data platform check out my video?here .

To stay up to date with the latest business and tech trends in data and analytics, make sure to subscribe to?my newsletter, follow me on? LinkedIn , and?YouTube , and, if you’re interested in taking a deeper dive into Snowflake check out my books?‘Mastering Snowflake Solutions’ ?and?‘SnowPro Core Certification Study Guide’ .

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About Adam Morton

Adam Morton is an experienced data leader and author in the field of data and analytics with a passion for delivering tangible business value. Over the past two decades Adam has accumulated a wealth of valuable, real-world experiences designing and implementing enterprise-wide data strategies, advanced data and analytics solutions as well as building high-performing data teams across the UK, Europe, and Australia.

Adam’s continued commitment to the data and analytics community has seen him formally recognised as an international leader in his field when he was awarded a Global Talent Visa by the Australian Government in 2019.

Today, Adam works in partnership with?Intelligen Group , a Snowflake pureplay data and analytics consultancy based in Sydney, Australia. He is dedicated to helping his clients to overcome challenges with data while extracting the most value from their data and analytics implementations.

He has also developed a signature training program that includes an intensive online curriculum, weekly live consulting Q&A calls with Adam, and an exclusive mastermind of supportive data and analytics professionals helping you to become an expert in Snowflake. If you’re interested in finding out more, visit?www.masteringsnowflake.com .