Today's customers don't just want things fast. They crave unique experiences. They want immediate delivery updates for an order they placed a minute ago, and they want their music app to instantly understand the type of songs they like. Business leaders want to understand their customers faster and automatically tailor the user experience. They want to track sales, inventory and customer onboarding immediately. To meet the demands of modern businesses and today's customers, there needs to be a shift from the traditional data warehousing approach to a real-time technique.
Businesses aiming to deliver superior digital experiences, retain customers and innovate rapidly must seek ways to get value from data faster, and this is where real-time data warehousing helps.
Real-time data warehousing involves the continuous process of loading data into a warehouse and making it instantly available to the different business functions that require it. This is unlike the traditional data warehousing approach, where data is loaded in batches overnight or hourly schedules from source systems. Having up-to-date information readily available is a game-changer for businesses and offers these significant benefits.
1. Faster decision-making
Real-time data warehousing enables organizations to consolidate data from different sources, extract insights from them and leverage them to make strategic business decisions faster. Organizations can refresh data from all business systems in the data warehouse in real-time and set reports to run on an as-needed basis. This saves the time required to generate reports and analytics for more agile decision-making.
Executives spend 37 percent of their time making decisions, and more than half of this time is wasted, according to a McKinsey survey of more than 1,000 organizations. For managers at an average Fortune 500 company, this could translate into more than 530,000 days of lost working time and roughly $250 million of wasted labor costs per year. This survey suggests a strong connection between fast, effective decision-making and positive business performance.
Pitney Bowes, a global ecommerce logistics company improved its decision-making after switching to a real-time data warehouse. Before moving to a real-time data warehouse, they had to rely on daily overnight batch processes to consolidate inventory and sales data. This resulted in them being unable to make important personnel and cost decisions regarding the orders being fulfilled. By switching to real-time data warehousing using Fivetran and Snowflake, Pitney Bowes can consolidate data in real time. This helps them understand how to make business decisions immediately rather than waiting for the previous day's information to come through.
2. Enhanced data democratization
Real-time data warehousing promotes the democratization of data where everyone in the organization can access the current and historical data they need to carry out their duties and optimize their initiatives. According to a Wakefield study, only 13 percent of companies report being able to derive value from newly collected data within minutes or hours.
Findings from a Google Cloud/Harvard Business Review paper shows that democratizing access to data and analytics across the organization is crucial for the success of businesses, as stated by 97 percent of industry leaders surveyed.
Providing access to real-time data for everyone starts with enabling data to be rapidly ingested into the data warehouse. Having real-time data has cascading effects on everyone across the organization. For example, data engineers can quickly model data for analysts and data scientists, analysts can extract insights from data rapidly, and data scientists can immediately apply machine learning capabilities against real-time data. Also, a real-time data warehouse can be connected to data visualization tools like Tableau and Power BI to serve sales, finance, customer service and marketing teams.
Beyond internal data access, real-time data warehousing fosters data democratization between different organizations. Alex Biller, VP of Platform at Snowflake at the Modern Data Stack EMEA Conference, presented the example of automakers collaborating with telecommunication companies to increase network coverage by exchanging GPS and cellular data from linked vehicles in real-time.
3. Personalized customer experiences
Real-time data warehousing provides the foundation for advanced analytics and machine learning essential to providing personalized customer experiences across all channels an organization uses.
According to research by Accenture, 91 percent of consumers say they’re more likely to shop with a brand that provides offers and recommendations relevant to them. McKinsey's research also indicates that companies that excel at personalization gain 40 percent more revenue than their average counterparts. Leading companies like Netflix, Spotify and Amazon have grown rapidly and retained customers by providing personalized experiences for customers.
For example, say you’re creating an elearning application and want to create a personalized user onboarding experience for your customers based on the actions the user has taken. In this scenario, a continuous data stream feeding from the product database could indicate if the user has selected action A (current career goal). You can then read that event immediately to the real-time data warehouse and combine that with other events like the user's education, work experience, or industry. Based on all this information, you can create tailor-made learning paths for the user, making the app experience meaningful for the customer. By combining real-time data and machine learning, you can gain insights into the customer's actions and tailor the onboarding experience accordingly.
4. Improved business agility
Real-time data warehousing improves the speed at which businesses can respond to changes. It reduces time lag in business processes helping organizations to be more agile and take advantage of opportunities faster. Real-time data warehousing helps companies immediately spot opportunities and adjust their strategy across different aspects of the business, boosting efficiency and allowing them to meet their revenue and profit goals.
For example, if you own an ecommerce website running a Black Friday sale, real-time data warehousing can allow for immediate adjustments to advertisements and sales prices by gaining real-time insight into customer and market data, thereby improving profitability.
Take World Fuel Services (WFS), having grown enormously in the past ten years through more than a dozen subsidiaries, WFS needed to get a global view of the client list in the different subsidiaries to help them identify new business opportunities and make decisions quickly. By leveraging real-time data warehousing with Fivetran and Snowflake, WFS was able to retrieve a unified customer list across all business units. This master list was then used for lead generation purposes across subsidiaries and business units, leading to upsell and cross-sell opportunities. This new capability has so far generated more than 300,000 new leads for WFS.
Additionally, real-time data warehousing was critical in helping WFS navigate the initial days of the COVID-19 pandemic. When the travel and fuel industries were hit as an effect of the pandemic, WFS decided to retain revenue flow by increasing account receivable efforts for services already rendered. The problem, however, was that accounts receivable information was spread across dozens of ERP and billing information services across the company’s subsidiaries. Real-time data warehousing with Fivetran helped pull data from several disparate sources into a centralized database that provided a unified view of money owed to the company. The result? The company was able to closely track its receivables every day, gaining visibility over millions of receivables that were previously inaccessible.
Also, since real-time data warehousing moves data continually, businesses can quickly spot data loading issues, fix them and prevent potential data processing errors. This approach is different from traditional data warehouses, where if the nightly batch job fails, it may take the next batch window to recover, leading to time and resource loss.
5. Unlock new business use cases
Access to data in real time can unlock a plethora of use cases for businesses across every industry. It has the potential to change how businesses operate and the value they can deliver to their customers.
- Multinational food chain Nando’s uses real-time data to effectively create data-driven marketing campaigns to reach customers.
- Penn Medicine uses real-time interactive dashboards to help it more efficiently identify when patients are ready to come off ventilation.
- Lufthansa Systems, a division of Lufthansa Airlines, uses real-time information to optimize flight planning and determine the most effective flight routes in terms of cost, fuel and time.
- Online design platform Canva uses real-time data to gain a 360-degree view of its customers and the business, enabling them to be more efficient with customer acquisition and retention.
- Factories can use real-time data to track the health of machines in the factory to ensure optimum performance, facilitate predictive maintenance and prevent unplanned disasters.
- Streaming services, social media channels and ecommerce platforms use real-time analytics to build recommendation engines to provide customers with better product recommendations and assistance.
- Sporting organizations like the NBA and NFL use real-time data to provide teams with a per-minute analysis of player performance and team performance. This helps teams to track player progress, improve team output and monitor players' health at the moment.
Data replication enables real-time data warehousing
Real-time data warehousing is becoming increasingly relevant and essential for companies that want to leverage data to remain competitive in this fast-paced digital era. However, to gain the benefits of real-time data warehousing, companies must first focus on access to data in the first place and properly implement their data replication solution.
Whether you’re consolidating operational data from multiple databases to a central data warehouse like Snowflake, BigQuery or Databricks for analysis and business intelligence or moving data between on-prem and cloud data warehouses in real-time, data replication helps guarantee continuous copying and synchronization of data between source and target systems to fuel real-time data warehouses.
If you need a head start on data replication, there's no better place to look than Fivetran. Fivetran enables log-based change data capture, a data replication technique that identifies changes made to data in a database and delivers those changes in near real time to target systems. Fivetran delivers data as frequent as five minutes if your data volumes permit.