Data Exchange leads to Secure Data Collaboration

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By Vimal Venkatram, Country Manager, Snowflake

In a global digital economy, real-time data analysis is closely related to business success. Companies that effectively leverage their data are able to position themselves as leaders regardless of the industry. With data-driven insights, businesses maintain a competitive edge, improve company performance and deliver strong user experiences. To match the pace of business, companies need to establish transparent and data-driven relationships. In India, as one of the largest and fastest growing digital market, companies are accelerating their technological adoption to maximize the value of their data. NASSCOM estimates that by the year 2022, cloud spending in India will reach $7.2 billion, growing at a compound annual rate of 30 percent. With the help of big data technologies such as cloud, companies are able to respond to the market’s ever-changing needs.

Unfortunately, wider adoption of technology is often met by roadblocks. One of the challenges many companies face is the existence of data silos. Without effective data integration strategies, the free flow of information within the organization as well as with partners, vendors, suppliers and customers can be hindered. This impedes collaboration and prevents companies from getting the most out of their data.

Companies waste away valuable resources by using traditional data sharing methods like emailing spreadsheets, carrying out batch processes with file transfer protocol (FTP) or the extract-transform-load (ETL) method and application programming interface (API). As these data sharing methods are not secure, scalable and does not support real-time updates, companies end up having stale copies of data scattered across the organization’s data landscape.

The answer to this conundrum is data exchange. With its cloud-built architecture, data exchange eliminates the need to move or copy data. Those who are granted access simply reference the data in a controlled and secure manner, including across regions, cloud providers, and even companies. Data exchange is the demolition tool that break down data silos and change how organizations acquire, leverage, and monetize data. They enable discovery of trusted data sets, control and management over data consumption, metrics on data usage, and monetization of data.

With data exchange strategies, companies can enhance their data sharing and collaboration capabilities and derive the most benefits from their data. Here are four ways data exchange supports secure data collaboration:

  1. INTRA-COMPANY STRATEGY

Many organizations, especially multinational and global companies, struggle to share data across business units, departments, locations, and subsidiaries. By breaking down internal data silos, businesses can facilitate data flow across the digital ecosystem and improve operational efficiency. A central data repository that houses all of the company’s data results in better internal collaboration and productivity, stronger data-driven insights, and faster time to market.

  1. CROSS-COMPANY STRATEGY

In a global economy, collaboration with external partners, suppliers, vendors, and customers spurs growth and productivity, improves business relationships and delivers new insights. However, this requires data sharing that keeps proprietary data safe and secure. The cross-company strategy provides the means to invite other organizations to publish and access data with established data control guidelines and monitoring capabilities. By having secure data exchange capabilities with external organizations, businesses can improve collaboration and open up monetization opportunities.

  1. DATA SOURCING STRATEGY

Organizations searching for new sources of external data and ways to reduce data analysis costs should look at their data sourcing strategies. In some industries, companies gain a competitive advantage by using external data. Unique external data sets that complement internal data can help generate better insights through richer analytics. However, sourcing external data at scale in a governed way can be challenging. A data sourcing strategy enables data vendors to publish their data sets within a company’s central portal where data scientists can access and evaluate the data to determine what to acquire. This gives the business visibility into data usage, ensure security, and enable informed decisions to improve future data acquisition and usage.

  1. DATA DISTRIBUTION STRATEGY

Data providers looking for ways to share data externally and monetize data assets at scale to create new revenue streams need to create a strong data distribution strategy. While it can be challenging for data providers to grant direct data access to customers and to personalize data feeds, a cloud-enabled data exchange platform will help deliver better customer experiences and increase retention. Secure data sharing allows data providers to create and host a walled garden of shared data. Customers can access data securely through the online data portal and have a personalized experience through monitoring and data usage tracking. Moreover, data exchange platforms also reduce costs and improve margins by removing reliance on APIs or FTP.

  1. HYBRID STRATEGY

A hybrid data exchange strategy is not uncommon for businesses. Many customers fall into the hybrid category because data exchange removes data limits and open up new business opportunities. The hybrid strategy allows an organization to benefit from multiple data collaboration scenarios and demonstrates the limitless potentials offered by data-driven insights.

To craft a data exchange strategy that matches the needs of the business, a secure data sharing platform is essential. With the help of a secure, cloud-based data collaboration solution, businesses are able to securely share data with customers, break down data silos and have control over their invaluable data assets.

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