A data warehouse is a storage space or facility for all data about a company’s history over the span of its existence. There are many reasons for keeping a data warehouse. But the most important reason is for making informed decisions about the future of your business.
What is a Data Warehouse?
A data warehouse is a database of historical data about the history and performance of a business or enterprise. Though the name suggests a physical "warehouse," a data warehouse can refer to any sort of repository that stores data records. The data housed or stored in a data warehouse is helpful for creating analytical reports mapping the trajectory of the business and helping it strategize for the future. Some businesses have a single system for their data management. Others have a separate data management system for transactional history and business analytics.
What is Business Intelligence?
The term "business intelligence" refers to any practices with the goal of collecting, integrating and analyzing data or other information that can be accessed to make decisions in the best interest of the business. Business intelligence may refer to software, technologies or other tools that gather and analyze data. It can predict which tools may benefit the business. Business intelligence practices analyze sales records, hiring histories, expenses and other financial decisions that have affected the business over time. This data indicates which choices and procedures may have contributed to the company’s success or failure in specific areas.
Why Your Business Should Care About Big Data
For many businesses, big data can be confusing and a little scary. Big data are culled from digital and more traditional sources both within your company and externally. These data are the raw materials that will undergo continuous scrutiny and analysis. Whether you consider social media interaction or focus only on transaction-related data, big data matters because it reflects your company’s history and predicts where your company is going.
A variety of data are compiled for analysis. Unstructured data are text-heavy rather than quantified. These data are nontraditional interactions and initiatives the company has taken to achieve its goals. Social media interactions, level of customer engagement and website posts are unstructured data. This data can be difficult to interpret with traditional analysis models or database tools.
Multistructured data, on the other hand, refers to advertising data, transactional data and data from web-based interactions with consumers. Big data are critical for companies who need to analyze various data streams to change their performance or develop new strategies. Any company interested in increasing profits, connecting with their audience and growing within an innovative industry should be interested in big data.
Ashley Friedman graduated from Sarah Lawrence College in 2003 with a Bachelor of Arts in Creative Writing and Social Sciences. She has experience writing copy for the websites of creative professionals, and regularly contributes to several blogs covering popular culture, travel, food, and social action.