The Data and Information Management industry is in a disruptive era and new technologies and architectures are emerging. With this disruption in the market driven by emerging big data startups, the technologies available are growing and require a high level of understanding and technical know how to identify which solution is a best fit. Decision makers are often influenced by vendor marketing and messaging or recommendation from their influencer network and not based on a thorough research. That being sad, big data became a cornerstone for all businesses of different sizes across all industries.
We believe that being data-driven is a journey where companies continue to learn how to better use data as a tool to create meaningful and emotional experiences. Successful companies and governments in the 21st century are using such tool to build data-driven products. That’s why we need to see how our own culture could tailor this tool to be used collaboratively in building a smarter governance ecosystem.
Data Strategy is the first step to build such ecosystem. We are strong believers that successful data projects are business-driven and starts with business goals and not with a Hadoop or Spark cluster. That’s why, we focus our efforts in defining needs for the whole business along to identify data mashups which takes into account your business situation and what kind of use cases you can implement based on your maturity. We bring together business and IT stakeholders to show the value in the data strategy.
We use our secret magical soup stone recipe to achieve three goals which are articulating the business goals that can be achieved using data. Second, with an experience of training thousands of people and experience in different cultures, we use our very own sensemaking tools and techniques that can transform a culture to become data driven. Third, we won’t leave you without a solid roadmap on how you can get started with your data projects.
Traditional data strategies only focused on specific technology goals to reduce costs and achieving certain benchmarks. Data strategies now focus on build a next generation data-driven organization that understand data as an asset to remain competitive and flourishing in the 21st century.
Organizations in the 21st century aim to become data-driven. However, being data-driven is a journey where companies continue to learn how to better use data as a tool to create meaningful products and experiences. In order to define a data-driven organization, we need to look at different levels of maturity to make that claim.
Here are our top six signs of data maturity:
– Full Interoperability: Data-driven organizations need to achieve both technical and organizational interoperability. Organizational interoperability contains aspects like organizational strategies and policies, laws, business processes, cost, and collaborative work while technical interoperability deals with data lineage, semantics, and infrastructure.
– Team Sport: Data-driven companies believe that data science is a team sport. That’s why, they organize datathons and competitions and also engage in other data science meetups and help the whole organization to be part of the data-driven product development workflow.
– Organizational Data Natives: In the 21st century, data natives and data scientists need to have diverse skills including meaning making, creativity, curiosity, patterns recognition, storytelling and empathizing. These skills are the key to build a data-driven ecosystem.
– New Data-Driven Mindset: We are moving from predetermined questions to a world of narratives and exploration that help us discover questions we didn’t know we had. You do not need to throw away years of investment and experience in other technologies, we can augment our data warehouse and traditional BI technologies with new technologies and not replace it. It is a new age. We need a new mindset!
– Agile: Developing quick wins is the best way to get executive buy-in for your big data projects. Mature data-driven organizations need layers of decision surfaces from the far edge of sensors up and into the cloud. The needs for differing data management and analytics processes and goals will continue to evolve at every layer to be able to act at the right time and context.
– Data Science is your company’s core engine and the tool for your arts…Being data-driven is a way of living in a disruptive way. It is is not focused on the “huge” amounts of data nor on a Hadoop or Spark Cluster.
At this stage, we interview key stakeholders and conduct assessment workshops and capture current readiness and desired big data analytics maturity and then capture business needs to align with big data offerings.
We work closely with Chief Data Scientists and business analytics managers to build business use cases across all industries for Big Data, IoT and Smart Cities that can be presented to top management to get investment and buy-in. The business case will include a presentation report for executives with financial study and ROI.
Vendors: We work closely with software and hardware vendors who are developing Internet of Things, Fog Computing, Big Data, and Smart City platforms and infrastructures to help them develop compelling business use cases on top of these ecosystems.