10 Actionable Data Trends in 2023 To Nail Your Analytics

With the evolution of cloud services and the opportunities it created to move huge workloads to the cloud, data and analytics has tiptoed into every techies’ life. In the age of artificial intelligence and machine learning, big data has made a huge impact across data intensive industries such as healthcare, retail and ecommerce, government, and banking. 

From database as a service (DBaaS) to natural language processing, big data analytics’ tsunami waves have shaken the foundations of the technology industry. According to a Capgemini surveyOpens a new window , 27% of business executives say that their company’s big data initiatives are profitable. Despite the green grass on the big data’s side, data leaders have concerns when it comes to big data challenges such as data integration, lack of technical expertise, and proliferation of data silos. We asked data leaders to share actionable trade tips to make data more accessible and scalable for enterprises in 2023 and beyond. Here are 10 massive data trends:

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1. Infuse Data Ethics Into Business To Protect Customer Privacy  

Stijn ChristiaensOpens a new window , co-founder and chief data citizen, Collibra

“Major data breaches happen nearly every week, which means organizations must do more to fight them. Not only do breaches result in a major financial loss for companies, but they can also destroy customer trust.

“In 2023, organizations must infuse ethical data practices by prioritizing the protection of customer privacy and the use of data in a compliant, transparent manner. This can only be done through a company-wide approach that starts at the top. All employees should be trained in data ethics and required to follow high standards when it comes to the use of company and customer data.”

2. Boost Your Spending To Protect the Integrity of Big Data  

Samir SherifOpens a new window , CISO, Absolute

“In 2023, organizations will boost their spending to protect the integrity of big data. Data has become the lifeblood of almost every organization- we rely on it to problem solve, plan our businesses and product roadmap, and serve our customers in the best possible way.

“In 2023, threats to organizations and individuals will evolve in order to erode our trust in data to run our businesses. We’ve seen this sort of tactic before with the rise of deepfakes- mutilation of information and big data to create a sense of mistrust in our own resources.”

3. Improve Big Data Quality With AI & ML Workflows  

Danny ShaymanOpens a new window , machine learning product manager, InRule.com Opens a new window

“Enterprises can enhance their artificial intelligence and machine learning strategy by using automation to continuously update reports and improve data quality. Using automated data workflows to drive adaptive AI systems will enable enterprises to automatically identify changes in customers’ preferences and anticipate their needs, dissatisfaction or satisfaction with a product or service. 

“In verticals like retail, data can be updated instantaneously based on real-time interactions to improve AI-backed decision-making. However, this method is dependent on the ‘source of truth’ behind what really happened. In other words, ML models predicting churn, returns, fraud or loan defaults may be limited to adopting on a less frequent basis.”

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4. Emphasize on Regulations With a Focus on Responsible Data  

Arnab MishraOpens a new window , chief product officer, Xactly

“In 2023, utilizing first-party data will continue to be a critical business asset due to its ability to foster more personalized recommendations to customers, a key component for growth. Additionally, artificial intelligence will be more widely used to empower organizations to proactively predict future performance indicators, allowing leaders to drive higher performance, plan better, and ultimately improve their bottom lines.

“Moreover, responsible data will be top of mind for companies, meaning that there will be greater importance on regulations that ensure principles of transparency, ethical and effective management of personal data for operational use.”

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5. Tap Into AI/ML Tools That Enable Easy Processing of Data  

CF SuOpens a new window , VP of machine learning, Hyperscience

“The symbiotic relationship between data, artificial intelligence and machine learning is a force to be reckoned with in the enterprise ecosystem. Increasingly, these algorithms are generating more accurate insights as the influx of data is digested. When thinking about data strategies, AI/ML can effectively process and improve the data fed into an organization’s system.

“For example, Intelligent Document Processing (IDP) backed by AI/ML can interpret characters from unstructured data like PDFs, emails and messy handwriting, effectively turning unstructured information into actionable data that can be used for downstream decision-making. Enterprises must tap into AI/ML tools that enable the easy processing of data without burdening employees, turning static numbers and information into usable insights.”

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6. Propel Big Data Analytics With Microservice Architecture  

Anthony BulkOpens a new window , director, data and intelligence, NTT DATA

“The top three big data trends for 2023 that will bring value to businesses are deep automation across the entire data value stream, microservice architecture patterns applied to big data, and the rise of online data marketplaces. Deep automation across the data value chain is required to power data-driven enterprises and produce positive outcomes at the speed of business without sacrificing quality.

“Microservice architecture patterns will also be key, as they enable agility and innovation in data and analytics, which in turn will propel automation. Finally, online data marketplaces will be driven by the increased need to buy, sell and trade data with ease.” 

7. Go Beyond Tech and Address People-Based Aspects of Data Management   

Myles GilsenanOpens a new window ,  VP of data, analytics and AI, Apps Associates

“One of the main challenges data executives will face in 2023 is deciding how they will leverage data to gain a competitive advantage. The ‘cloud wars’ have given way to the ‘data wars.’ To stay ahead of competitors, companies will need to improve the success rate of their AI and ML projects as disciplines like MLOps and related toolsets are helping AI/ML to have more of an impact beyond the data lab.

“To improve operations, organizations must go beyond technology and address the structural, cultural, and people-based aspects of data management—embracing disciplines like ‘data mesh’ and DataOps.” 

See More: How to Combat Data Silos

8. Invest in Data Lakehouses To Enable Real-Time Reporting

Chris DyckOpens a new window , research lead, Info-Tech Research Group

“Solution providers are investing more in data lakehouses and data fabric to gain better access to enterprise data, enabling real-time reporting and analysis for speedier, data-driven decision-making. Companies need experts that deeply understand all the variables in play to improve products and services and make cost-saving determinations. Data and analytics tools are more effective when they go hand in hand with industry experience.

“There have been more advancements in data accessibility, which reduces friction and drives more value for the business, as it allows users to see updates in real-time to make more timely decisions.”

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9. Leverage Vision AI To Create Insights From Video Data  

Yamin DurraniOpens a new window , CEO, Kamivision

“One of the primary big data trends for 2023 will be creating value and actionable insights from video data, at scale by leveraging vision AI. New advances in computer vision, usable AI and Edge technology are making it easier than ever to build vision AI models that solve problems across industries like creating safer environments and improving operational efficiency and productivity.

“For example—retail footage can track customer flow and analyze behavior patterns; video data can be leveraged to ensure worker safety and enforce compliance; and senior citizens can retain autonomy while detecting falls. These tools reduce human error and create business efficiencies.”

10. Build Quality Into Your Data Stream and Operations  

Steve ZiskOpens a new window , senior product marketing manager, Redpoint Global

“The rise in relevance, use, and influence of data quality is set to bring tremendous value to businesses in the year ahead. A company must have a holistic, real-time understanding of its customers to deliver valuable touchpoints and interactions, which necessitates high quality data sets. 

“Big data leaders are finally building quality into their data streams and operations after recognizing that analytics and engagements are only as relevant as the quality of big data available. Companies who use data quality procedures to enhance customer connections are already reporting improved retention and profitability, as well as better customer satisfaction scores.”

See More: Data Initiatives To Guide Enterprises Through The Great Resignation

Which big data trends will be adopted by your enterprise in 2023? Comment below or let us know on Opens a new window LinkedInOpens a new window , FacebookOpens a new window or Twitter Opens a new window . We’d love to hear from you!

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