Turning data into a strategic advantage
To transform data from a burden into an advantage, improve data management strategies, break down data silos, invest in analytics capabilities and build a data-driven culture.
- Stephen Catanzano,
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Enterprise Strategy Group
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Data-driven organizations are drowning in information. They often struggle to handle their extensive data collection, which can result in fragmented systems and inconsistent information that creates missed opportunities.
Research from Enterprise Strategy Group, now part of Omdia, showed that 73% of organizations collect data from 50-499 sources every day. Data becomes valuable when organizations manage it effectively and use it strategically. Without proper management, data becomes an expensive liability, which impedes business expansion and prevents innovation.
Turn data into an asset
Enterprise data should no longer be considered a byproduct of business operations. The purpose of data extends beyond recording historical events and now serves as an instrument for forecasting trends, customizing customer interactions and supporting strategic business decisions. To harness this potential, organizations must undergo a basic transformation in their thinking: They should elevate data management from a technical task to a crucial strategic necessity. Organizations must allocate resources to building infrastructure, establishing processes and hiring skilled personnel who can manage data collection, storage, analysis and utilization.
Break down silos
The most significant obstacle in transforming data into an asset is eliminating data silos. Having data distributed among multiple departments and systems prevents businesses from achieving a complete understanding of their overall operations. The presence of isolated data systems creates potential errors and prevents effective teamwork between different company functions. Organizations must break down silos and bring data into more centralized data platforms.
The elimination of duplicate data alone can bring massive cost savings for organizations, in addition to having a strong ability to discern what data is valuable to empower the business and serve as a foundation for AI and analytics. Data platforms such as Cloudera, Nasuni, Databricks and Informatica can help get data organized. Cloudera's True Hybrid capabilities can also manage data where it lives, whether on premises or in the cloud.
Focus on data quality
After centralizing data, organizations must focus on maintaining accuracy and completeness. Flawed insights and poor business decisions often result from inaccurate or incomplete data. A focus on data quality management processes is required because they help detect and fix errors while ensuring data remains consistent and maintains its integrity. Clear data governance policies and metrics must be in place, and organizations should use automated tools and technologies to perform data cleansing and validation.
AI plans highlight data management importance
Enterprise Strategy Group research showed that 71% of organizations are planning to introduce 11 or more generative AI applications in the next 24 months using retrieval-augmented generation to couple their enterprise data with AI models. This demonstrates the importance of your data management strategy and ability to build a trusted, secure and governed data foundation for every use case.
Visualize and analyze
Once organizations have built trusted data sources and they have the ability to extract valuable insights from the data, it can shift from being a cost burden to having measurable ROI. Organizations must invest in data analytics capabilities, including data visualization tools and statistical modeling. Through data analysis, businesses discover hidden patterns, trends and anomalies. Apply these insights to develop strategic plans, improve operational processes and customize customer service. Some vendors offer built-in analytics capabilities, and others such as Qlik and Domo specialize in analytics and visualization. Cloudera AI offers a complete platform to test, develop and deliver generative AI tools such as AI agents and chatbots.
Change the culture
Another aspect of moving data from a liability to a strategic asset involves a culture shift. Organizations must educate employees about data significance and equip them with the tools and training to establish a culture that encourages curiosity and experimentation. This starts with the people and systems that enter structured and unstructured data into databases and systems.
The accuracy and quality of this data is the starting place toward a successful program. Tools for data quality, observability and governance can continue to refine the data. On the other end of the spectrum are the data users who must have confidence in their data. Enterprise Strategy Group research found that only 48% of organizations completely trust the data they use for decision-making. There is clearly a lot of room for improvement in most organizations.
Stephen Catanzano is a senior analyst at Enterprise Strategy Group, now part of Omdia, where he covers data management and analytics.
Enterprise Strategy Group is part of Omdia. Its analysts have business relationships with technology vendors.
