According to a recent report by Allied Market Research, the global market for data warehousing is expected to rise to $34.7 billion by 2025, which is almost double its worth of $18.6 billion in 2017. What fulfills the needs from investment in data warehouse development in an organization?
The role of innovative applications and practices in an enterprise has increased the need for Cloud data warehouse technology, which boosts the efficiency and lessen the costs across company functions. Today, various departments like marketing, finance, and supply chain operations take advantage of modern Data Warehouse Consulting as much as the engineering and data science teams do.
Types of Data Warehouse
There are three main types of data warehouses that the users have been using worldwide, which are:
- Enterprise Data Warehouse
- Operational Data Store
- Data Mart
Why is Data Warehouse Development Necessary?
Here, explore the list of five business needs that can be fulfilled with bigger investments in modern enterprise data warehouse development.
1. Need to Access and Act on Data in Real-Time
Nowadays, businesses can do data processing and detecting signals in real-time that had much higher latency in traditional systems. Identifying the stock levels at retail stores, for example, lets a retailer respond to customer trends and solve key concerns before they negatively impact the business. Superior yet, by merging a real-time vision of supply chain data and weather, the retailer can restock stores running vacant before it goes empty.
Modern data warehouses make data visibly understandable, meaningful, and actionable in real-time by implementing an extract-load-transform (ELT) method over the single omnipresent extract-transform-load (ETL) model, in which the cleaning, transformation, or enrichment of data on an external server before loading is done into the data warehouse. With an ELT approach to working, raw data is explored, drawn and analyzed from its source and loaded, comparatively unchanged, into the data warehouse, enabling it to be a lot faster to use and analyze.
2. Search for a Holistic View of the Customer
In the past, the information existing in a company about its customers was collected in siloes. The data from one source would be stored in a data silo, and data from another source is saved in a data lake or stored in an on-premises traditional system. Without a simpler approach to connecting the dots, it was complicated to make sure that high-value customers were getting the best experience that’s possible.
The assurance of a data lake strategy is that complete information of your company, whether it is structured, semi-structured, or similar to raw data, can be rapidly and easily queried from a single place. With this approach, a data warehouse for an enterprise can facilitate an absolute view of the customer, supporting to improve campaign performance, reduce churn, and eventually, to develop revenue. An enterprise data warehouse also enables predictive analytics, where teams use situation modeling and data-driven predictions to inform marketing and other business decisions.
3. Recognizing Data Lineage to Ensure Regulatory Compliance
In huge organizations, it becomes tough to discover the origin of specific data. This situation can give rise to problems, particularly for the finance and accounting department, when they conduct audits. Traditionally, the only recourse they have to file is a support request that can be expensive and slow. A modern enterprise data warehouse allows its data customers to audit and examine data sources directly and locate errors rapidly.
You can also implement compliance through the General Data Protection Regulation (GDPR) presented by the EU with the use of a modern data warehouse. When you don’t have a data warehouse in your system, it is likely that your company would have to set up a difficult process to fulfill every GDPR request. This process would engross various functions or business components, looking for relevant PII data. Therefore, you’ll essentially have to search in only one place with a data warehouse.
4. Allowing Non-Technical People to Query Data Rapidly and Cheaply
Developing a data warehouse can also profit your non-technical personnel in job operations beyond finance, marketing and the supply chain. For example, architects and store designers can improve the experience of the customer within new stores by digging deep into data from IoT devices located in available locations to recognize which parts of the retail stores are most or least engaging. Global service managers can support their decision-making on whether to extend retailing outlets or move product lines on a powerful set of information that includes data regarding hiring and retention of employees, in addition to typical metrics like cost per square foot.
5. Need to Join Data Together into a Single Location
Nowadays, many data sets are simply too huge to move and query faster and in a cost-effective manner. To restrain expenses and latency, some companies use regional clouds. According to research, for companies that use a multi-cloud strategy, 81 percent of them end up with data spread across multiple platforms from contending cloud providers. Getting rid of these obstacles is the main concern for organizations that struggle to be data-driven.
With a modern data warehouse, users can integrate various data sources, applications, and departments together to combine all information in a single location, allowing authorized users access anywhere, anytime. Therefore, managers can leave the worries of maintaining the data on their own and making it available to all business users in real-time.
Data Warehouse technology has made things easier and allowed the organization to create a single storehouse for their data and providing a unified view of data to its users. In this way, the security and privacy of data are also ensured as only the legal users are allowed to access sensitive information, including important credentials, which are kept safe from hackers.
Top-class Data Warehousing Consulting will help you to understand how companies can store data across various regions and cloud providers and query it as an inclusive unified data set. Thinking of developing your enterprise data warehouse? Get advice from the data experts and make your data easily manageable and accessible! ExistBI offers Data Warehouse consulting services in the United States, the United Kingdom, and Europe.