The ever-growing digitalization of our world has created a massive amount of data about nearly every aspect of our lives. Every internet site (including this one), click, search engine term and purchase is recorded and associated either with our online identity or in a cookie. Not to mention the devices; smartwatches, smart home devices and the Internet of Things. Though all wonderful pieces of technology, the net effect is that the service providers know an amazing amount of information about us: more than we might imagine. So the question is, why not use the same core techniques on operational system business data? Here’s where a data strategy enters the picture.
Simply put, a data strategy is a roadmap and plan to utilize a company’s data and to support access, collaboration and quality. Most importantly, it identifies the purpose and why your company is putting the strategy in place.
Unfortunately, compared to execution, strategy is the easy part. Here are 5 steps to help execute your data strategy
- Identify: Look for areas in your business with the highest quality data. It’s no wonder most data initiatives start with financial data as it’s the most critical to business. Next, move to structured operational data as it’s low hanging fruit. This step also includes the selection of tools and methods to automate the collection, publishing and management of content.
- Deliver and Share: The key to this step is to determine the vehicle (files, transactions, data streams, etc.), content and formatting. This component also defines methods to allow data availability, support for internally vs. externally delivered content, change control and interface/access to allow delivery.
- Stage and Store: Areas to consider for staging and storing enterprise data include what to store (transactional history, application data, etc.), the tools and technologies to be used for storage (DBMS, flat files, cloud, etc.) and the access method (API, Web services, applications, etc.).
- Transformation: Consider the movement and transformation of source data carefully as it’ll be used by downstream systems. Determine the data movement/migration toolset to be used for bulk data movement and processing and application/transaction messaging.
- Governance: What are your company’s policies for managing the data? Data governance methods should cover information access and resolving conflict. Data management practices should incorporate the adoption of data standards and the deployment of data policies into applications and data usage.
Thinking about data strategically can be a little daunting at first. There are a lot of decisions to deal with, and it can be overwhelming if you’re not careful. But if you go in with a plan, and really understand the strategy that you’re implementing, you can turn your plethora of raw data into real, usable information that can grow your company. Enter Lantern Data Systems We only specialize in business intelligence solutions for the construction industry and we know both inside and out. Our solutions transform data into valuable information to help construction companies grow.