Successful data-driven companies rely on data to derive valuable insights and use the information to make game-changing decisions. Businesses use data and document conversion services to organize and manage big data, which includes both structured and unstructured data. Today, the conversation is about smart data rather than big data. Making data smart is necessary to harness its power effectively, according to experts.
What is Smart Data?
Smart data is data that provides valuable and actionable information to support important business processes. In simple terms, smart data is data which makes sense.
Over the years, companies have invested money in amassing large volumes of data from different sources. But more data is not better data and does not necessarily equal new intelligence. Information overload has become a challenge. Businesses have come to realize that what they need is not big data, but smart data that provides value for important processes and functions such as demand forecasting, pricing, labor optimization, and driving competitive advantage
“If big data is about volume, speed, and variety then smart data is more focused on creating value, meaning, and accuracy (veracity) for some sort of purpose or outcome”, explains Study.com.
Smart data is data from which signals and patterns have been extracted by intelligent algorithms and can be easily used in business models to deliver value quickly. While in traditional analytics where data is processed on some fixed schedule, smart data is accessed and transformed for analytics in real-time at the time it is collected.
With smart data, companies can:
- Identify and predict new market trends first
- Better understand customer expectations and make improvements,
- Make smarter and faster decisions
- Recognize the right growth opportunities
Starbucks is a classic example of an enterprise that has leveraged big data in smart ways to improve the customer experience and their business.
Building a Smart Data Strategy – Important Considerations
- Develop and Document a Clear Smart Data Strategy: Create a strategy that aligns with the goals of your business. Define the measurable milestones that you want to achieve with regards to program management, data architecture efficacy and business usage and benefits. To obtain a true understanding of its current data culture, a company also has to document how it defines, obtains, archives, enhances, deploys, disseminates and uses its data.
- Pay Attention to the Data Source: It’s important to identify the data sources that provide the latest and relevant data, says a netscout.com blog. Avoid tools that use unstructured machine data which has to be sorted and produces only old data. The article recommends using wire data as it gives a complete for network visibility about what is going on and done right, and can be accessed, collected, and transformed in real-time.
- Build Specific Use Cases: A data smart organization has to create specific use cases that translate to true business value (inc.com). Make a list of your main goals and identify individual use cases that can provide the greatest return on investment. Consider data preservation and architecture, data ownership and governance, data lifecycle, safeguards/protections and risk.
- Ensure Data Quality: Smart data starts with reliable and verified data. IBM estimated that bad data costs U.S companies three trillion dollars a year. As smart data is used for critical purposes, organizations need a proper strategy to build quality data. Data cleansing services are a practical option. The data cleansing process involves removing/updating obsolete and incorrect information, and improperly formatted, duplicate, or irrelevant information.
- Review Need for Organizational Changes: To invest in a smart data strategy, organizations need to structure and prioritize their strategy to describe a smaller dataset that offers value and can be acted upon. They should adjust their corporate culture to enhance the understanding and adoption of smart data and implement a consistent approach to data quality.
- Adopt Automation: Embracing automation can help companies extract valuable information from their growing volumes of data.
Role of Document Conversion
The first step in a smart data strategy converting your existing data into digitized content. Document conversion companies convert paper-based documents into electronic format. Intelligent OCR technology is used to convert text in scanned images into text that can be edited and searched for in the file. With the help of a document data extraction tool, companies can extract data easily from file formats such as pdf, docs, tiff, png, jpg, and more. Document conversion offers many benefits:
- Automated document conversion speeds up data capture and prepares data for used in analytics applications.
- It provides useful, accessible and searchable smart data for better and faster decision making and plays a key role in a company’s overall digital transformation strategy.
- It results in searchable content that is accessible and suitable for deeper analysis, archival, and storage
- It can drive end-to-end business process automation by improving and speeding up data-heavy workflows, enhancing analytics, and promoting business process automation.
Success in digitizing your content depends on partnering with a company offering reliable data and document conversion services.