Data-Driven Enterprise

Enterprises worldwide want to maximize value from the vast amount of information they generate coupled with valuable external data. The core intent is creating business transformations and business impacts with action-driven insights. Constrained by existing legacy systems, data platforms, and applications, business leaders are looking for a transformation journey to modernize their systems. However, the challenge has been a lack of a holistic framework, approach, processes, and technology capabilities.

The journey to a matured adoption of a Data-Driven Enterprise culture requires sponsorship and ownership from senior leadership responsible for identifying the right initiatives (use cases), business objectives, and goals to be realized. With a business view of people and processes first and then technology, the enterprise identifies and prioritizes valuable data and analytics initiatives.

Celsior Technologies has found that the following key solution areas are important in moving to the data driven enterprise. We recommend them whether you make this journey alone or whether Celsior assists you with them.

1. Advisory & Foundation Services

Enterprise Strategy for adoption of Data and Insights
The key to the success of the Data-Driven Enterprise culture is to have a digital strategy coupled with an Enterprise Data Analytics strategy defined with a rationalized roadmap. Treating data as an asset and monetizing it to deliver business value will drive an optimized Data & Insights function. Defining high business-impact Data & Insight use cases will help drive modern data architecture with associated
technology and tools, transforming data to information.

Data Health Assessment
Data confidence and value are the key purposes of the entire data life cycle. The enterprise typically needs to do a health check of the critical data objects they own to understand the quality (accuracy, completion, etc.), availability, and usage of data. The outcome will help define and prioritize needed Data Analytics & Insights solution components and is the foundation of sustained success.

Modern Data Architecture
As enterprises embark on transforming their current legacy data platforms and associated processes to modern data architecture and platforms, they need a well-defined holistic approach. A clear needs analysis is needed to understand the maturity of the current legacy systems in terms of their design, ability to capture the necessary data, gap analysis, and future needs. Taking an enterprise view of this information, it is important to define the modernization approach, data platform migration, and corresponding people/processes with a clear focus on cloud strategy to drive efficiency and cost savings.

Centers of Excellence

All three of the above Data & Insights solution components address people, process, technology, and data. Defining, managing, and governing the necessary roles, workflows, standards, policies, etc. is the role of a Data & Insights Center of Excellence. The design and implementation of the formal organization and functions should include enablement and organizational change management and drive effective Data & Insights sustainability.

2. Data to Information

The Data to Information journey involves processing, aggregating, and organizing data. Leveraging repositories, ingestion, data quality, solution integration, and data transformation results in better, faster decisions and improved customer/stakeholder experience. This is the core of the entire data life cycle, wherein the data is cleaned, filtered, and transformed according to business/data rules to the desired repeatable model, structure, and format. Planned and structured ingestion of data includes core and master data, real time data, streaming data, IoT/sensor data, and social media. This unstructured and structured data is ingested into the enterprise and used to create the appropriate data repositories such as data lakes, data warehouses, analytical data stores, and models. This modern data architecture with data management is foundational to successful self-service capabilities.

3. Information to Insights

Information to Insights involves discovering, organizing, and analysing data and information to generate actionable insights and proactive decisions. Business insights are the understanding of a specific cause and effect in a particular context. Webster defines insight as “the capacity to gain an accurate and deep intuitive understanding of a person or thing”. Business insights involve data visualization, applying AI/ML algorithms, natural language technologies, and advanced scalable analytic models which can drive actions.

Data science governance of people, process, technology, and data is also necessary to sustain successful insight capabilities. Automating workflows, collaboration, data enrichment, and model reusability will enable business insights and thus drive competitive advantage for your business.

Why Celsior Technologies

• With a strong talent sourcing engine based on our parent company, Pyramid Consulting, we
can provide amazingly fast access to expertise in hot transformation areas
• Flexible, easy to do business with
• Ability to integrate Data and Insights with other Celsior solutions including Cloud & Data
Center, AppDev, Data DevOps, Security, and End-User design
• Holistic enterprise solutions from data ingestion to advanced analytics
• Strong experience in financial services, life sciences, manufacturing, retail

Case Study

A major healthcare testing and metrics company needed a more dynamic and scalable (up and down) IT environment. Obviously healthcare testing has taken on huge importance in the last couple of years with explosive growth. Colocation costs were increasing, and time and effort for internal IT resources to maintain and operate the environment were also increasing. This was taking time away from strategic,
higher-priority initiatives.

As part of the resulting effort to move to the cloud, the company wanted to migrate their mission critical applications from on-premises SQL Server to an Azure SQL managed instance. They also wanted to address intermittent timeouts and latency issues.

The Celsior solution included an integration strategy and an end-to-end plan for migrating the SQL Server database to Azure SQL with minimal downtime. We were able to scale down the burden of maintaining infrastructure and to establish a highly available environment.

The migrated environment reduced infrastructure cost by 40% and gave the company the flexibility to change resources online (CPU/storage). The database has 99.99% availability guaranteed.

In another project for the same company, Celsior rationalized and migrated numerous BI dashboards to Microsoft Power BI and improved usability, value, security, and performance. By virtue of the BI modernization, we improved performance by 60% and reduced report development effort by 40%.

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