Information management is the opposite of one size fits all. So many approaches exist, and it takes focus and deep knowledge to find the best fit. Our advisors can guide you through the many choices out there and find the path that makes the most sense for reaching your analytics goals.
When we create an information management advisory recommendation, we look at the whole picture. It’s not just about getting a database, data warehouse, or data lake set up; it’s about how those structures reinforce your wider analytics ecosystem and support you in getting the answers that set you up for success.
We’ll evaluate your infrastructure and help you decide which of the many project options we support works best for your organization:
- Data Warehousing: Centralizing data and normalizing structure to create a single, reporting-friendly platform
- Governance: Establishing data quality standards, core terminology, and common data workflows/promotion strategies
- Big Data: Creating solutions designed to handle both tradition structured and non-traditional unstructured/semistructured data types
- Managed Services: Installing, configuring, and maintaining information management environments both on-premise and in the cloud
Data warehouses look a lot different now than they did when Bill Inmon and Ralph Kimball were first pioneering this structural concept. Change and speed are the rules of modern data handling, and we’re growing new approaches to data warehousing that keep up with the new data formats and big data-oriented methods that are now central to many organizations.
We’ll work with you to understand the benefits you could gain from a central data warehouse, evaluate the data types that matter to you, and construct the workflows needed to efficiently bring any kind of information into a structure optimized for actionable reporting results. Data warehousing engagements can address a number of organizational needs:
- ETL or ELT workflow optimization and integration with big data assets
- Star or snowflake schema construction
- Installation and configuration of new data warehousing assets
- Just-in-time data warehouse development for data discovery
- Advisory evaluation of vendors and tools resulting in expert recommendations and roadmaps
The fastest way to scare someone in an information management conversation is to say the words “governance” or “master data management.” These terms conjure thoughts of multi-year projects that struggle to keep pace with business changes, but we think that’s unfair. Governance is something we should all be thinking about whenever we talk data and analytics, and when done right it enhances and ensures the success of projects instead of needlessly inflating them.
At Ironside, we make it a point to keep governance in mind during every step of infrastructure development, and we’re experts at implementing it in ways that streamline instead of bog down our clients’ environments. Applying these techniques as we define your priorities and information management structure leads to:
- High quality data
- Data discovery practices that build on your core data instead of polluting it
- A bimodal analytics strategy that moves smoothly between experimenting with new data and solidifying findings
- Overall efficiency through proven, tested processes for all your daily data management activities
Data formats and sources generating valuable data are two things that will only continue to increase as technology progresses. This is great news for analytics, but if you’re only looking through the lens of a traditional information management platform, it can quickly get overwhelming. That’s why our Information Management team has fully embraced big data approaches and can apply them to increase your visibility into and agility around the diverse data sources in your environment.
Our team can look across all the structured, unstructured, and semistructured data sources bringing data into your infrastructure and define a strategy that will sift through it all and capture the critical metrics you need to succeed in a timely fashion. An Ironside big data engagement’s goals are built around your specific data needs and can address any number of scenarios:
- Assessing big data technologies to fit your use case, both open source and vendor-based
- Designing a data lake to centralize all key data sources regardless of format
- Building or implementing distributed processing platforms such as Hadoop, Cloudera, Hortonworks, etc.
- Integrating additional big data software packages for specialized performance, such as Hadoop Ecosystem elements like Spark, Pig, Hive, etc.