With the new year events well behind us, we’re steadily focused on moving forward in 2021.
While we have seen a change in the calendar year, one initiative that continues to be a top priority for businesses is storing, managing, accessing and optimizing corporate data.
Given that, let’s consider what I believe will be some of the hottest technology trends that involve data management for the coming year.
Hyperautomation
Hyperautomation is the combination of automation tools needed for machine learning (ML) and automation. It handles the application of advanced technologies to incrementally automate business processes and augment human capabilities. Hyperautomation assists companies in visualizing functions and processes by creating digital twins that virtually replicate the systems used by a company. In return, this will provide real-time intelligence about the business.
Cloud Automation
Collecting data is the easy part, but tagging data sets, applying a taxonomy, and ensuring a good level of governance and compliance can require a number of resources.
The good news is that cloud automation can enable teams, IT and developers to create, change and optimize resources in the cloud by easing the amount of activity and burden of cloud systems, while performing complex tasks almost as easy as clicking a button.
AI, AI ops, and ML can help by reviewing large volumes of logs and data by identifying trends and analyzing potential outcomes. This approach can prevent and predict issues, while ensuring a capacity plan tackles excessive costs by merging or sunsetting unnecessary resources.
(Hybrid) Cloud Computing
Cloud computing has been a key transformational technology for more than a decade. However, a good amount of companies do not feel equipped or comfortable uploading their data on the cloud due to concerns about security, privacy and latency.
A hybrid-cloud deployment allows businesses to enjoy a high degree of flexibility. Using software to enable communications between a private-cloud service and a public-cloud service helps workload needs as costs fluctuate. The hybrid cloud can connect to several public clouds or to one or several private clouds, thus creating a simplified cloud infrastructure to a company’s computing workload.
Typically, a private cloud relies on an internal network available to a limited number of users while a public cloud is a computing service offered by third-party vendors. A hybrid cloud can improve developer productivity, increase security, support compliance with regulatory systems, boost innovation, augment efficiencies and provide a holistic approach to the network.
Augmented Data Management
Businesses proactively utilizing metadata, data fabrics and ML to simplify, connect, optimize, and automate data-management processes will be able to reduce time-to-data delivery by a significant amount over the next couple of years.
For context, data fabric uses continuous analytics over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of integrated and reusable data objects. This is done regardless of deployment platform or architectural approach.
Artificial Intelligence (AI) techniques are currently being implemented to recommend next course of action, automatic monitoring of data-governance controls and other processes.
Metadata is BIG (Data)
Many companies and organizations expedited digital transformation efforts in 2020, leading to an exponential volume of data types scattered throughout their organization.
As companies invest, scale and maintain their corporate governance, they will recognize that metadata plays a significant role in meeting standards and safeguards. Metadata will allow for deeper context into data sources, or the complete series of code that can be executed to determine its output. As metadata levels increase, enterprises will look at new and scalable solutions, while applying ML and AI to leverage it.
Actionable Data
Actionable data has been a common theme among business intelligence, customer experience, and analytics vendors for many years. This year provides an excellent and fertile market for Big Data’s potential to become actionable.
We should therefore understand that data-value depreciation accelerates rapidly as data gets older, hence, using data as soon as it gets created should become a key trend for businesses in 2021.
Data governance, collection, integration and visualization improvements have already created a useful framework to put data into action. IoT, the cloud, edge computing and instant digital channels that allow businesses to connect with customers instantly are now some of the technology combinations that provide for actionable data and incredible insights.
Data Warehouses/Data Lakes
The split between compute and data allows advantages for data lakes over data warehouses. Data warehouses have had, in the past, other advantages over data lakes. This is meant to change due to a variety of new open-source innovations in the data tier.
Given that, I see three major trends that could take place in 2021.
First, the comeback of the meta-data layer, embedded AI, automated analytics and new and simplified query interfaces designed for business users.
Second, the comeback of data layers, as foundational elements of analytic solutions, will be required to support governance and expandable data assets. With smart meta-data layers, optimized user interfaces will allow business users to manipulate data in a more intuitive approach, thereby saving valuable time to insights with no requirements for analytical skills.
Third, AI and dynamic analytics will move from the enterprise domain towards software vendors that include these capabilities and enable market adoption via their customer base.
Data Natives Join the Workforce
A whole generation raised on data – think of exercise, sleep, your music platform algorithm (etc.) – will begin to join the workforce. Their infused ability to make sense of data will have a major impact in the way we work today and into the future.
Also, data-literacy skill sets and curriculums in academia will help organizations become more analytical and innovative. We’ve already seen great progress in Europe in the data-literacy space.
Natural Language Processing (NLP)
NLP is defined as the interaction of human language and technology. A few of the more popular examples are Alexa, Siri and Google Home. In addition, NLP is the front-end to an AI backend where voice requests can be translated into actionable data results.
NLP keeps growing at an incredible pace just as voice search keeps growing exponentially. With billions of people in the world currently using voice-activated search and assistant, it is expected that voice search could make up half of all searches worldwide very soon. NLP helps by collecting and processing voice-based data so it can be actionable internally for those who need to access it via voice orders.
Democratization of Technology
Look for further growth in data democratization. Generally speaking, democratization of technology, also known as “citizen access,” refers to providing people with easy and affordable access to technology without extensive training. This field focuses on application development, data and analytics, knowledge, and design.
Regarding data, many believe that by allowing data access to anyone in a company, in every business unit, at all levels of responsibility, that they will be empowered to use data to strengthen their decision-making.
Internet of Things (IoT)
IoT is a significant trend as devices are pieces of electronic equipment embedded into smart phones, industrial equipment, and monitoring equipment. Some have estimated that there are more than 25 billion active IoT devices in the field.
IoT devices collect information and transmit it to a central location for aggregation and analysis. This data is then mined to generate data insights, alerts and trends that can be used to reduce costs, increase automation and efficiencies, and forecast new business opportunities.
Data Security and Compliance
As businesses attempt to minimize data breaches and data loss and risks, data security makes the list as a top trend again this year.
Data-management solutions help IT to have greater visibility and insights to investigate and remediate potential threats. In parallel, data-management solutions enable enforcement to real-time controls to ensure regulatory compliance related to data protection.
Wrap Up
There are numerous trend stories that lay out expectations and predictions for the coming year, but I thought it would be important to focus in on data management. Time will tell, but these are some of the hottest trends that I see developing over the coming year.
