There’s a lot of conversation in the industry about how data is key to unlocking powerful decision-making capabilities. Data can ignite a wildfire of change, creativity, innovation, speed, and agility across an organization.
But decision makers have to be completely confident in their data in order to leverage these kinds of influential capabilities. Data has to be trustworthy, unbiased, accessible, and timely for it to generate meaningful, analytics-driven insights. Companies need to derive purpose and value from both data and analytics, especially in this time of uncertainty, using a unified data management and analytics solution.
Ronald van Loon is a SAP partner, and is applying his unique position as an industry analyst to take a deeper look into what different organizations are doing in the data and analytics space.
Cloud, artificial intelligence (AI), machine learning (ML), database and data management, application development, and analytics are pillars of transformation today. As organizations look to future-proofing their business, they have some critical decisions to make when it comes to unified data management and analytics solutions that meet their individual needs.
With this in mind, we’ll explore vendor differentiators to help executives better understand the market so they can develop and benefit from their data and modernize their data architecture to support changing and emerging requirements.
Emerging Data Management and Analytics Trends and Evolving Business Requirements
What are today’s organizations looking for in a data management and analytics solution?
- Greater agility, simplicity, cost-effectiveness, and ease of automation to accelerate insights.
- The capabilities to overcome challenges surrounding traditional on-premise architectures that inhibit organizations from meeting emerging business needs, including those pertaining to real-time analytics, complex data sets, self-service, and high-speed data streaming.
- The ability to surpass pervasive data challenges through the strategic application of both existing and new technologies to drive next-gen analytics.
- The ability to move beyond cumbersome data warehouses that typically demand a multi-year commitment to build, deploy, and gain advantages.
This reflects a few critical trends that are supporting the movement towards a unified data and analytics strategy. Businesses are migrating or extending to the cloud, with 59% of enterprises anticipating cloud use to exceed initial plans because of the pandemic. Also, data lakes and warehouses will begin to assume similar qualities as the technology grows. Finally, according to SAP, companies will transition to “data supermarkets” to manage data consumption to clarify processes.
As a modern architecture, Data Management and Analytics (DMA) reduces complications related to chaotic, diverse data via a reliable model that includes integrated policies and adjusting to evolving business requirements. It utilizes a combination of in-memory, metadata, and distributed data repositories, either on premise or in the cloud, to provide integrated, scalable analytics.
Data Management and Analytics Solutions Per Vendor
DMA adoption is increasing as organizations make efforts to benefit from the next evolution of analytics, introduce more collaboration across teams and departments, and transition beyond data challenges. When evaluating a DMA solution, there’s a few key elements that organizations should keep an eye out for, including:
- Self-service capabilities that allow business users to ask questions to support decision making, drive data intelligence and aid in rapidly ingesting, processing, transforming and curating data through ML and adaptive intelligence.
- Real-time analytics through the streaming of multiple sources, and performance at scale for diverse and large-scale project types.
- Integrated analytics to help businesses better manage various data types and sources. This extends to storing and processing voluminous sets of both unstructured and semi structured data, and streaming data.
Organizations must also be able to leverage their DMA solution to support analytics-based processing and transactions across use cases like data science investigation, deep learning, stream processing, and operational intelligence.
There are several vendors in the domain who are offering data and analytics solutions to suit a wide range of use cases, though the following is not by any means a complete list:
Microsoft’s Azure platform suite offers a range of cloud computing services across on premise, hybrid cloud, and multicloud for flexible workload integration and management. They also provide enterprise-scale analytics for real-time insights, and visualizations and dashboards data collaboration.
SAP offers a complete end-to-end data management to analytics solution with SAP HANA Cloud, SAP Data Warehouse Cloud, SAP Data Intelligence, and SAP Analytics Cloud. These solutions are SAP Unified Data and Analytics and they coordinate data from multiple sources to fast track insights for business and IT and give data purpose.
Amazon Web Services (AWS) offers numerous database management services to support various types of use cases, including operational and analytics. They’re the largest global cloud database service provider, and offer cloud provider maturity, scalability, availability, and performance.
The Google Cloud Platform (GCP) includes numerous managed database platform-as-a-service solutions, including migration and modernization for enterprise data. They offer built-in capabilities and functionalities for data warehouse and data lake modernization, and both multi and hybrid cloud architectures.
Snowflake’s Cloud Data Platform is a solution that offers scalability for data warehousing, data science, data sharing, and support for simultaneous workloads. It includes a multi-cluster shared data architecture, and enables organizations to run data throughout multiple clouds and locations.
Empowering the Data Journey with Unified Data and Analytics
Unifying data and analytics can be problematic for organizations across industries due to increasing data sources and types, messy data lakes, unexploited unstructured data, and siloes that impede insights.
Both business and IT teams need trustworthy, real-time insights and fast, seamless access to data to make sound, data-driven decisions. But business and IT worlds are often fragmented when they should be harmonized, and respective data and analytics needs often conflict, which can prevent a data culture from flourishing.
The business side stresses data accessibility and self-service, while IT wants to strengthen data security and governance. These competing needs have to be balanced to support interdepartmental collaboration and maximize data effectiveness and productivity.
The SAP Data Value Formula conveys how each component of the SAP Unified Data and Analytics, the foundation of the SAP Business Technology Platform (SAP BTP), works cohesively to give data purpose:
This enables organizations to leverage capabilities to develop, integrate, and broaden applications and gain faster, agile, valuable data-driven insights. When different data sources are brought together in a heterogeneous environment, with a hybrid system for cloud and on-premise, business and IT departments can better collaborate to work towards shared organizational objectives. Basically, the end-to-end data journey is supported to help transform available data into actionable answers.
Unite All Lines of Business
All aspects of a business can benefit from unified data and analytics, from finance and IT to sales and HR. Siloes are eliminated to facilitate an organization-wide approach to data and analytics, business and IT are united to accelerate data-based decisions, and data journeys are charged with agility and high quality data.
You can register for the SAP Data and Analytics Virtual Forum to learn more about powering purposeful data, or sign up for the SAP Data Defined: Monthly Bytes newsletter to stay on top of the latest data and analytics trends and developments.