As data stores grow exponentially, companies are using new entity matching tools and technologies to integrate data.
Master data management (MDM), cloud integration and microservices are all part of the rapidly changing face of data integration. As organizations respond to customer demands for a unified experience, seamless data integration is becoming paramount. In the first part of this two-part series, we examined key concepts in big data such as real-time integration, NoETL and data lakes. In this second half, we’ll look at how conglomerate, legacy and orchestration layer trends influence data integration.
Master Data Management (MDM)
Most enterprises have a variety of systems handling different parts of the same data. This situation is common, especially when companies merge or takeover another entity. Each company may have similar — or even duplicate — data that must be combined. The goal of MDM is to create one master copy of each data entry, which is then used by downstream applications throughout the organization. Trends in MDM include focusing on entity resolution, assigning stewardship of data and technology, prioritizing security, integrating business processes and workflows, and making metadata available across data stores and applications. In truth, MDM is extremely difficult. Even companies making a dedicated effort to integrate their separate data silos report the process is long and tedious. But new tools are helping ease the transition, resulting in better use of data assets and more effective business decision-making.
The cloud era began 10 years ago. Today, Forrester estimates the market for public cloud services will grow from $146 billion in 2017 to $178 billion in 2018, and expand after that at a 22 percent compound annual growth rate (CAGR). Hybrid cloud arrangements, using both public and private cloud installations, grew from 19 percent to 57 percent in the last year.
Now that cloud adoption is ubiquitous, cloud integration is the primary focus. More companies are moving critical data to the cloud, increasing pressure on data managers to ensure data security and accessibility. Tools like HiPER can perform entity resolution in the cloud or securely behind your firewall. Deployed in the cloud, it offers efficiency and scalability. If your organization has strict compliance and security protocols, it can easily be installed in your private cloud as well.
Unlike traditional monolithic systems, microservices architecture creates software apps that act as independent services. They employ loose coupling, standardized interfaces, opacity and composability. Many organizations currently use a data integration setup that extracts, transforms and loads data for analysis and processing. In contrast, microservices create small systems that move the processing closer to managers and staff.
Integration is faster, easier and more flexible, and allows your business workers to pull data using business language rather than computer jargon. Microservices are used to make monolithic systems more agile and effective, as well as for brand new applications and projects. Most organizations use multiple platforms and technologies for microservices, preferring different tools for various challenges.
Data integration is entering a new phase. Speed, agility, flexibility and utility have moved to the forefront as organizations deal with a hyper-competitive marketplace. Although traditional systems will always have a place as they perform vital tasks reliably, as data stores grow exponentially, companies are using new entity matching tools and technologies to integrate data. The process is faster and more accurate, helping company management and front-line workers use data to grow sales and build profits If this all seems a bit over your head, don’t worry, we’re here to help. Give Black Oak Analytics a call at (877) 805-0736 or contact Black Oak Analytics online today so that we can take care of your data concerns.