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Business intelligence data integration

We’ve heard it time and time again, and a quick Google search can confirm: data is the new oil, currency, gold — the list goes on. There’s no doubt an organization’s most critical asset is its data.

Access to business intelligence (BI) data is especially essential for companies looking to transform their customer experience; they need to be able to understand who their customers are, their customers’ needs, and how customers interact with the company to create positive experiences and stand apart from the competition. This is why a customer 360 doesn’t stop with just collecting BI data; a great 360-degree view of the customer should be thought of as a holistic system of systems, constantly refreshed to help move the customers along the desired journey. Likewise, delivering a seamless and high-quality customer experience involves the entire company ecosystem, including its partners and channels.

 

The challenges with ETL and ELT

With the rise of machine learning and SaaS applications, IoT devices, social media, and more, real-time business intelligence data integration is core to analytics-driven organizations. Ask yourself, in today’s world, how helpful would it be to have analytics from only 50% of your data sources? Or how about one-to-two-month old analytics about your business? By the time you collected information from all the disparate data sources and crunched the numbers, your market opportunity may have passed you by.

Today’s BI data sources are more distributed, and as companies look to a range of both cloud-based and on-premises enterprise applications – including enterprise resource planning (ERP), human resources (HR), and customer relationship management (CRM) systems – it’s inevitable that the mixing and matching of unstructured data from disparate sources and connecting multiple databases will become extremely complex.

Traditionally, organizations turned to ETL (extract, transform, load) or ELT (extract, load, transform) for business intelligence data integration. Essentially, ETL and ELT provide organizations with the same outcome: actionable insights from relevant data that they want to analyze. Using BI-oriented ETL processes, businesses extract data from highly distributed sources, transform it through manipulation, parsing, and formatting, and load it into staging databases. From this staging area data, summarizations, and analytical processes then populate data warehouses and data marts.

Both of these approaches are widely implemented. However, as the IT landscape transitions to the cloud, lack of visibility into the internals of cloud databases and applications often make it impossible to implement ETL-based integration. And when data integration happens after the fact – typically in either interday or intraday batches – the results of this business intelligence data integration are likely outdated.

Another strategy some businesses implement is custom code, a method in which skilled developers write and implement code within each specific endpoint in order to create connectivity. This requires extensive knowledge of each endpoint, and as the number of endpoints increases, it becomes a grueling task. Custom integration also leaves room for errors, leading to the need for additional support and maintenance costs. Moreover, as organizations take advantage of mobile, cloud, and SaaS applications to power their business, their IT ecosystem grows in complexity. With more and more endpoints requiring connectivity, this approach to business intelligence data integration becomes a complex and fragile “spaghetti architecture.” All of these errors can result in inaccurate BI data and inefficient business processes.

While these approaches were once widely acceptable, businesses are now constantly seeking insights into how well they are performing, spotting problems or anomalies in their tech stack, and making quick decisions about how to maximize resources. To be competitive, companies can no longer wait for this data. Time is now measured in milliseconds, not minutes, hours, or days.

The need for a new BI data integration approach

The transition to the cloud means greater value is placed on real-time business intelligence data integration updates, something ETL tools cannot easily deliver as they are, in general, not designed for “always on.” They are primarily batch-oriented, and for each batch, ETL tools set up connections, parallel processes, load the data into memory, and conduct data quality and transformations. There is usually a start and an end to each ETL job.

Conversely, a modern globally distributed workforce requires 24/7 real-time query and access to business insights and analytics based on up-to-date data. From fraud-detection and customized ads to recommendation engines, predictive diagnostics, etc., organizations are increasingly collecting new forms of data in real-time. Instead of processing server log files hourly, companies want to know what went wrong now. Instead of daily customer preference reports from website clickstreams, companies want to deploy customized ads and deals to the current customers while they are visiting the site now. Other use cases include trading stocks using large-volume real-time data streams, network monitoring, smart grid and energy conservations, etc.

Further, many organizations are facing setbacks because traditional approaches to implementing ETL/ELT create a patch work of legacy and modern systems, abandoned code, and duplicate work. Learning new query interfaces and hand-coding custom business intelligence data integration could mean waste of precious IT resources and slow development. This is why some organizations are turning to a new solution to implement these approaches.

MuleSoft’s Anypoint Platform provides API-led connectivity with real-time integration. Unlike traditional ETL tools used for BI data integration, Anypoint Platform isolates applications and databases from one another, providing an abstraction layer to reduce dependencies by decoupling systems.

Anypoint Platform, offering both real-time and batch capabilities, is a flexible solution for businesses in need of both. For example, retail companies expanding their eCommerce presence are constantly updating their massive online product catalogs with detailed information (SKUs, inventory, specs, reviews, etc.). A modern architecture can leverage Anypoint Platform to facilitate data flow from various sources, which could expose the most up-to-date product info to web and mobile apps and other applications through APIs, designed and managed by Anypoint Platform. At the same time, some data and processes may still be better fit for batch mode, such as master data that might reside in traditional databases and would be moved in batch in big data use cases.

Beyond providing users with the ability to easily aggregate and transform business intelligence data, MuleSoft’s Anypoint Platform also offers Anypoint Exchange, a repository of pre-built generic protocol, transport, database, SaaS, and legacy application connectors. There are hundreds of connectors available on Anypoint Exchange — from those created by MuleSoft to those created by partners and the community.

Connectors provide simplified and consistent connectivity to applications, enabling developers to focus on data transformation, as opposed to writing onerous custom code and connecting to a data store. Available connectors include those for Salesforce, SAP, Workday, NetSuite, ServiceNow, Hadoop (HDFS), Kafka, Amazon S3, and more, providing businesses with instant access to business intelligence data residing in disparate applications and service. MuleSoft’s integration solutions allow users to easily clean up data, ensuring data accuracy and eliminating duplication. Moreover, these solutions enable businesses to consolidate data and create a single view of the company, its products, and its customers.

Anypoint Platform can help businesses capitalize on their most valuable asset in order to improve business agility. Contact us today to see what business intelligence data integration solutions MuleSoft can offer your organization.

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