Recently, Gartner released ten major technology trends in the field of data and analysis, providing guidance for data and analysis leaders in response and recovery to the new crown epidemic (COVID-19), and preparing for the restart after the epidemic.
If data and analysis leaders want to continue to innovate after the epidemic, they need to continuously increase the speed of data processing and access, expand the scale of analysis, and win success in unprecedented market turmoil.
Data and analysis leaders should check to try the following ten data and analysis trends to speed up the recovery after the new crown epidemic:
Trend 1
Smarter, faster, and more responsible AI
By the end of 2024, 75% of enterprise organizations will switch from artificial intelligence (AI) pilots to AI operations, and the number of analysis infrastructures based on streaming data will increase by 5 times.
Currently, AI technologies such as machine learning (ML), optimization, and natural language processing (NLP) are providing important insights and predictions on the spread, response effects, and impact of the virus.
Other smarter AI technologies such as reinforcement learning and distributed learning are creating more adaptable and flexible systems for handling complex business situations. For example, agent-based systems can model and simulate complex systems.
Trend 2
The decline of the dashboard
Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click data creation and exploration. Therefore, the user's time to use the predefined dashboard will also be reduced. The shift to dynamic data stories that support technologies such as enhanced analytics or NLP means that the most relevant insights will be streamed to each user based on the user’s scenario, role, or purpose.
Trend 3
Decision intelligence
By 2023, more than 33% of large enterprises will hire analysts to implement decision intelligence including decision modeling. Decision intelligence brings together multiple technologies such as decision management and decision support. It provides a framework to help data and analysis leaders design, establish, coordinate, implement, monitor, and adjust decision-making models and processes for business results and behaviors.
Trend 4
X analysis
"X analysis" is a general term created by Gartner, where X refers to the data variables of various structured and unstructured content (such as text analysis, video analysis, audio analysis, etc.).
During the new crown epidemic, AI played a key role, combing through thousands of research papers, news materials, social media content, and clinical trial data to help medical and public health experts predict the spread of the disease, formulate capacity plans, and find new treatments Methods and determine the susceptible population. The combination of X analysis and other technologies such as AI and graph analysis will play a key role in the identification, prediction and planning of future natural disasters and other crises.
Trend 5
Enhanced data management
Enhanced data management utilizes ML and AI technologies to optimize and improve operations. It also facilitated the transformation of the role of metadata, from assisting in data auditing, lineage, and reporting to supporting dynamic systems.
Enhanced data management products can review a large number of operational data samples, including actual queries, performance data and plans. Using existing usage and workload data, the enhanced engine can adjust operations and optimize configuration, security, and performance.
Trend 6
Cloud becomes inevitable
By 2022, public cloud services will play a vital role in 90% of data and analysis innovation. As data and analysis go to the cloud, it is still difficult for data and analysis leaders to achieve coordination between services and use cases, which increases unnecessary governance and integration expenses.
The key to data and analysis issues has shifted from the cost of a certain service to how to meet the performance requirements of the workload in addition to pricing. When going to the cloud, data and analytics leaders need to prioritize workloads that can take advantage of cloud capabilities and focus on cost optimization.
Trend 7
The collision of data and analysis
Data management capabilities and analytical capabilities have traditionally been regarded as different fields and need to be managed separately. Suppliers that use enhanced analytics to provide end-to-end workflows blur the line between these two markets.
The collision of data and analysis will increase the interaction and collaboration between these two traditionally relatively independent fields. This not only affects the technologies and capabilities provided, but also affects the people and processes that support and use them. Related roles will also expand from traditional data and analysis to information explorers and citizen developers.
Trend 8
Data market and trading platform
By 2022, 35% of large enterprises will participate in data transactions through formal online data markets, and this proportion will be 25% in 2020. The data market and trading platform provide a unified platform for integrating third-party data products and reducing third-party data costs.
Trend 9
The application of blockchain technology in data and analysis
Blockchain technology solves two challenges in the field of data and analysis. First, the blockchain provides a complete lineage of assets and transactions. Second, the blockchain provides transparency for a complex network of participants.
In addition to limited Bitcoin and smart contract use cases, a ledger database management system (DBMS) will provide a more attractive option for individual corporate audit data sources. Gartner predicts that by 2021, ledger DBMS products will replace most licensed blockchain usage.
Trend 10
Relationships lay the foundation for data and analytical value
By 2023, graph technology will promote rapid contextualization of the decision-making process of 30% of global enterprises. Graph analysis refers to a series of techniques used to explore the relationship between different entities of interest (such as organizations, people, and transactions). It helps data and analysis leaders find unknown relationships in the data and view data that is not easy to analyze with traditional analysis techniques.
Source: Gartner Corporation
Recommended reading
Big data becomes a new driving force to promote high-quality economic development
Data is "oil", and new production factors are written into files to release important signals
"Which industry development models will 5G change?
What will "new infrastructure" change