Think about data warehouses and the images that invade your imagination are that of large, unwieldy data stores- tough to navigate and unsuitable for real-time analytics and agile decision making. Somewhat true, yet not the complete picture. Usually, organizations make decisions without obtaining the complete picture from their data. Successful businesses develop data-driven strategies and plans, and turn out to be the differentiators. It boils down to building a data-driven culture. Just like technology that can’t be transformative unless you know the strategy to achieve it, you need to figure out the recipe to get the most out of your data warehouses.
Getting the Most From Data Warehouses
Building a team of specialists: The best way to develop a data warehouse is to integrate the efforts of internal IT specialists with full knowledge of the company's workflows with external consultants.
Integrate a Data Model
The value of your data is in its ability to extract insights. Doing so is directly related to your ability to ask questions. Therefore, before you start your journey to unify all your data, ensure that you integrate a data model that applies context and meaning to simplify data transformation into insights.
Make Sure the Data Is Clean
The data comes from multiple sources and is not always appropriately validated when taken from public sources. To make sound data-driven decisions, the information should be free of errors, outliers and cropped results.
Having Back-ups in Place
When systems fail, data warehousing can cripple organizations. It's crucial to have a backup runbook in place to continue to operate, get the data you need, and evolve even if there's a blip in the network.
Build on A Secure Foundation
For a data warehouse to be safe, it must have a strong cybersecurity foundation and undergo network security testing. When a breach or hack occurs, companies that fail to take this step will be mired in chaos.
Adopting an Agile Data Warehouse Methodology
Data warehouses don't have to be huge, monolithic, multi-quarter/yearly projects. If Data Warehouse projects are strategically planned and aligned to a single integration layer, they can be broken down into smaller, faster deliverable pieces that return a value much more quickly. By using an agile Data Warehouse methodology, you can also prioritize the Data Warehouse as your business changes.
Having a complete documentation of all the source tables, staging tables, and derived tables is essential to gaining actionable insights from your data. It is possible to design an ETL (Extract, Transform & Load) tool that captures even the data lineage.
The Many Benefits of Data Warehouses…..
- Having a grasp of business trends and making better forecasting decisions.
- Data Warehouses are designed to ingest and process enormous amounts of data.
- The structure is more accessible for end-users to navigate, understand, and query.
- Queries are easier to build and maintain in data warehouses.
- An efficient method to manage demand for lots of information from lots of users.
- Provides the capabilities to analyze a large amount of historical data
- Enhances data quality
- Improves Business Intelligence
- Enhances data security
How's the Future Placed?
For its many advantages, an enterprise data warehouse still wrestles with data integration, data views, data quality, optimization, and competing methodologies. Automation of data warehouses can reverse this scenario. Emerging technologies will be the fulcrum to the emergence of more capable data warehouses.
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