Modern business requires effective data solutions that allow for decision-making, efficiency and strategic planning. But a wealth of varied data sources overwhelms businesses, making it difficult to gain valuable insights and quickly respond to customer feedback, changes in the market and internal alerts. Fortunately, there are many tools to manage data that can help.
The first step of the process is to catalogue and categorize data assets. This will help identify which data assets require strong governance, can be replicated centrally and can benefit from self service access. This helps prioritize improvements without stalling innovation. It also provides the entire company with data literacy.
Identify and correct errors, inconsistencies and inaccuracies that may occur in data via cleaning and standardization processes. This improves data quality and usability, which is a prerequisite for advanced analytics, AI and enables more reliable data-driven decisions.
ETL (Extract Transform and load) is a method which combines data from multiple sources and transforms them into a more organized format, and transfers them to a central storage system or data warehouse. The data is then made available to be analyzed. This solution enables faster and more efficient processing, increased scale and retrieval speed.
Massive amounts of raw data in one, large-scale repository for faster processing and quicker access. A centralized repository can also support real-time analytics to respond more quickly to customer interactions or market fluctuations and internal alerts. Data warehouses can be scalable, flexible and cost-effective options for storing structured and unstructured information. Hybrid storage helps you achieve a balance between cost, performance and the ability to scale by using various kinds of storage to meet your specific requirements for data.
