How businesses make decisions, and the data analytics trends affecting them, has drastically changed during the pandemic.
This is largely caused by the health and safety restrictions affecting how we conduct our daily lives. Work, leisure, and even our spending habits have digitally shifted. And it is this digital shift that has magnified the significance of the role that Data Analytics plays in decision making.
Data Analytics helps brands, businesses, and organizations adapt fact-based decision-making to help accelerate growth. In our previous blog posts, we talked about the pros and cons of working with big data as well as the data analytics tools that you can use. To give you even better insights, here is our fearless forecast for the Top 5 Data Analytics Trends to consider for your strategy this year.
One fool-proof way of staying ahead in your industry is to make your processes as fast and as seamless as possible. Automation makes this possible through the use of data analytics and data engineering platforms and software to perform analytical tasks programmatically. An example of this would be a platform producing data visualization reports with minimal human intervention. This is a must for data science teams looking to do multiple projects for different business units simultaneously.
Manufacturing, retail, financial services, travel, and hospitality are among the fields which are benefitting from this trend. In a nutshell, automation is all about trading out mundane activities for processes that are more efficient.
Smart and Scalable Analytics Platforms
In the Covid-19 pandemic, historical data may not be as relevant as it used to be. Today’s data sets contain thousands, if not millions, of data points and sources. “Cleaning” and preparing data for deeper analysis can be repetitive, but it is a requirement for business units to have actionable insights.
Combining Automation with Big Data will make it possible for businesses to reduce manual tasks.
Apart from helping in automating tedious processes, Automation can also help create solutions that are highly adaptive, faster, and safer. Data Scientists and Data Engineers can use platforms with integrated machine learning to create models that can specify data sets that can be used for better decision-making. Platforms can also scale to the size of any company and can pull data from different sources, from social media platforms to CRMs.
Big Data, Analytics Platforms, and Automation are trends that are great to implement in your business strategy. But what can further help you along in your analytics transformation journey is asking the right questions regarding the use of your data.
Are you effectively collecting your data? Do you have the tools and processes to manage your data efficiently?
You can answer these questions, and learn more about the opportunities and challenges working with data through our big data management webinar. Click the button below to get free on-demand access!
Data Fabric is described as an architectural framework and set of data services that allow data management and consistent capabilities to be standardized across different cloud environments. It allows organizations to break down data silos and to unify their data sources across multiple business units. This also allows for greater data discovery and governance to be shared across any location or time zone.
Technology in business today, from self-service data consumption to faster and more secure data preparation, entails highly complex processes and integrations. Data fabrics can be the tool that businesses and organizations can rely on to reuse and combine different integration styles, data hub skills, and other technologies.
While the importance of User Experience has always been talked about, it is only in the last two years that B2B organizations are really starting to recognize its significance. All data users want something that is simple and useful. They want seamless and engaging interactions with their analytics tools that would help them maximize their use.
Good user experience can help in handling technical difficulties and manual tasks. This will allow users to concentrate more on practicing good data storytelling. It makes it easier to put together data elements in a way that shows the big idea stemming from cohesive narratives. Put simply: it allows analysts to focus more on creating useful insights from the data.
Data Visualization has easily captured the interest of the market from the get-go. It is able to assist brands, businesses, and organizations to see massive chunks of hard-to-picture data with more clarity.
With Data Visualization, decision-makers are able to make sound decisions through visually interactive methods. It heavily influences the methodology of analysts as it allows data to be observed and presented in the form of patterns, charts, graphs, and so on.
The logic behind this is simple: The human brain is designed to remember and interpret visual cues better. The visual perception portion of our brains, the visual cortex, is one of the fastest parts of our brain in terms of processing. Data Visualization can also help democratize the use and interpretation of data across an organization. Forecasting future trends for sales or identifying new business opportunities will be much faster when the decision-makers can easily interpret the data.
The common factor for these top data analytics trends is the need for seamless automation and execution across analytics teams and business units. These must be paired with advocates who will “champion” the use of these trends and ensure constant innovation in the organization. A good place to start is to encourage your experts in data analytics and engineering to get more involved in projects where data analytics can benefit the most.
Get started on exploring how data analytics can accelerate growth for your organization. Contact us to schedule a chat with us or you can explore our Amihan Analyze analytics platform to learn how you can get insights from your data.
Maddie Cruz is a content writer and marketing professional.