In the first installment of this series, we examined how mid-sized enterprises can quickly get started on their journey to data maturity by implementing an operational reporting platform in as little as 4 to 6 weeks. The target users for this type of data service are the mid-line operational managers looking for actionable, tactical insight into system operations. The next user group to reach on the data maturity journey are the decision-makers at the departmental level (finance, sales, marketing, supply chain, etc) who require strategic insight for planning and resource management. The architecture required for this next level of data analytics is the 2-tiered subject-oriented data warehou...
We have all seen how more and more companies are moving to the cloud for their data management platforms. Snowflake, Azure Synapse, AWS Redshift, and Google Big Query are leading this charge towards low-admin, instantly scalable cloud database solutions. Accompanying this is a migration to cloud-hosted data integration and low-code ETL solutions like Matillion and Fivetran. It is tempting to assume that with all these low-overhead data management platforms the concept of data modeling may be a thing of the past, relegated to the pile of on-premise databases that this brave new world is supplanting.
In reality, data modeling is more important than ever. A key to understanding this importance i...
Enterprises running SAP Business Warehouse (SAP BW, BW/4HANA and BW on HANA) are keeping a close eye on challengers like Snowflake. Is cloud data warehousing the answer to all the challenges for organisations with a large SAP footprint? And how does a cloud data warehouse fit into the data architecture? Should it replace SAP BW or is there still value in SAP BW?
Why do most enterprises with a large SAP footprint run SAP BW?
The dominant position of SAP BW is easy to explain from a historic perspective, but it would not do justice to SAP BW to ignore its current strengths as well. Let us start with the latter. SAP BW is still the only data warehouse platform which delivers all data warehouse f...
In 2015, I was fortunate enough to lead the sales development effort of a cloud-based supply chain visibility product. The product was geared toward the manufacturing sector to allow a more transparent and collaborative platform to enable information sharing. We leveraged the Salesforce cloud to build the application, and it was intended to support digital transformation efforts within the supply chain to optimize the flow of information, provide real-time data to the supplier, empower collaboration, and scale for adoption. Unfortunately, the ability to execute on the vision failed and it was tied to one key component – the part on delivering real-time data.
Let’s fast forward to...
Growth companies today rely on Enterprise Resource Planning (ERP) systems to manage their daily operations and collect and retain vital business data. The ERP space continues to evolve . . . cloud-hosted ERP, AI-based automation, digital transformation, etc.; eventually an organization will find itself upgrading or migrating to a more modern enterprise platform. This move will likely involve a Systems Integrator (SI) specialist to drive the effort, and an SI’s focus may need to incorporate more than just the operational systems at hand . . . the organization’s approach to data integration and analytics should be accounted for as well.
Your SI and internal migration team will init...
Our recent blog series on the data integration portfolio introduced a variety of new architectures that help the enterprise manage their data resources, including replication, virtualization and cloud data warehousing. Organizations are now able to integrate multiple data management solutions to address a variety of business sources and requirements. But it is important to understand that the foundation of any enterprise data management portfolio remains the same . . . a roadmap to data management must be created that is independent of the underlying technology. This series of blogs will examine the three main elements of the data integration roadmap: the logical data model, master data ma...
For most of data warehousing’s history, ETL (extract, transform and load) has been the primary means of moving data between source systems and target data stores. Its dominance has coincided with the growth and maturity of on-premise physical data warehouses and the need to physically move and transform data in batch cycles to populate target tables efficiently and with minimal resource consumption. The “heavy lifting” of data transformation has been left to ETL tools that use caching and DDL processing to manage target loads.
However, the data warehouse landscape is changing, and it may be time to reconsider the ETL approach in the era of MPP appliances and cloud-hosted D...
This blog series has examined the hybrid data portfolio as a mix of technologies and approaches to a data foundation for the modern enterprise. We’ve examined a variety of strategies and technologies in data integration, including virtualization, replication and streaming data. We’ve shown that there is no “one size fits all” approach to an integrated data foundation, but instead have seen how a variety of disciplines that suit specific business and technical challenges can make up a cohesive data policy.
This final chapter puts it all together under the umbrella of “time-to-value" and its importance to the agile enterprise data platform. No matter what the techn...
Pandata Group's partners help us empower our clients and deliver value from data and analytics using the best technology for their particular business needs, which is why we're excited to announce we've added Snowflake to that list. After getting to know the Snowflake team and the ins and outs of their product, we see the immediate value Snowflake can bring to clients in search of a modern data warehousing solution.
- A fully managed, born-in-the-cloud data warehouse that delivers power, flexibility, and simplicity.
- Hosted on Amazon Web Services (AWS), the platform is elastic as you need it to be. Start small and scale as you grow. Conversley you can scale back, on-the-fly, as ...
What can EDA do?
EDA is the governed integration of disparate data collection applications, into a centralized “source of truth”, for enhancing business acumen to improve and optimize decisions and performance. EDA allows health plans to easily:
Analyze provider performance in order to optimize pay-for-performance
Evaluate treatment patterns across providers and better tailor care management program
Identify underlying opportunities for health education and intervention with high-risk members
Sustaining fixed EDA support and overhead costs can allow an organization to continue growth and improvement, thus providing an infinite return on investment (ROI).
Why do you need an EDA?