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Demystifying Data Integration for a Clear Business Win

Experts reveal how you can begin leveraging data integration to deliver value to your business, your customers, partners and wider organizational ecosystem.

Enterprises are creating billions of rows, articles and pieces of data every minute of every day. With multitudes of applications and information sources all creating mountains of data, ensuring the data is managed and delivered to the right team at the right time can be overwhelming.

Organizations must find a better, simpler way to access and analyze their data efficiently – doing so is key to making better data-driven decisions and winning in a saturated market. In the recent Demystifying Data Integration: Automation Hacks Every IT Professional Should Know webinar hosted by SnapLogic, a leader in intelligent integration and enterprise automation; SnapLogic industry experts Jeremiah Stone, Chief Technology Officer and David Wilmer, Principal Product Marketing Manager, broke down data integration.

From data integration challenges, the pros and cons of modern data integration methods, the benefits of automation and API management and how enterprise automation makes organizations more competitive in a cut-throat landscape; it’s a must-watch for any leader who wants to drive success for his/her organization.

The current state of data management

Data integration is critical to the success of organizations today. And yet, according to recent SnapLogic research in partnership with Vanson Bourne, 83% of ITDMs (IT decision-makers) are not completely satisfied with the performance and output of their data management and data warehousing solutions. This dissatisfaction stems from issues relating to data formatting, regulations and speed of data movement and accessibility within the organization.

“Organizations know that integrated data instills data trust and that trust is critical in basing important business decisions on analytics,” Wilmer says. “But regardless of data integration’s importance, many organizations are still finding it difficult.”

On average, enterprises have approximately 254 applications, 40-60 tools per team and more than half (56%) of SaaS applications are not owned or managed by a company IT department. As app sprawl increases, data from each app gets siloed and becomes inaccessible to other parts of the organizations, teams and apps.

According to the same SnapLogic research, more than half (53%) of respondents say they do not entirely trust their data for decision-making. Wilmer says this isn’t surprising, considering the number of disconnected data sources organizations typically have.

“At the same time, 40% don’t completely trust their data for decision-making because poor integration means data is missing or incomplete,” he points out. “Disparate data sources increase data silos. That means your data can’t flow between systems, which lowers the confidence in data.”

No data integration means no data insights, which leads to impaired decision-making – it’s an equation that adds up to adverse business outcomes and poor user experience. In fact, the average organization reports losing more than AU$1.45 million each year due to poor data management. To remedy this and leverage the power of SaaS, data must be integrated.

Breaking down modern data integration methods

To drive automation and better user experiences, data needs to be integrated across a variety of applications and systems within an enterprise. There are a number of ways to achieve that integration. However, many are complex and less than user-friendly.  Let’s take a look at some modern data integration methods.

Data Federation

An integration and access layer that sits atop disparate and distributed data sources and enables them to be accessed as if they were a single source.

  • Data stays in original sources
  • No need to migrate data
  • Lower cost
  • Latency delays when querying
  • Data and apps remain separate

Data Virtualization

A virtual database that serves as a data access layer to applications and requires similarly formatted data or strict data models.

  • Querying is faster than federated
  • Data needs to be formatted
  • May require data modelling
  • Not as fast as more modern ways

Data Lakes

Storage repository that becomes a destination for disparate data sources. Data is moved to the lake, which can be small or extremely large. Handles a wide variety of data formats.

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  • Deploy on-premise or in the cloud
  • Can serve as a central data repository
  • Data is easily accessible
  • Special skills required to manage
  • Data professionals must handle data
  • Slower query results
  • Can become data dumping ground

Modern Cloud Data Warehouses

Data warehouses perform all the heavy lifting to transform non-relational data files into a relational structure that makes it easier and faster to extract and analyze data.

  • Supports multiple formats
  • Uses column formatting
  • Faster access and analysis
  • Separates storage from compute
  • Can integrate with data lakes
  • May be better to separate out data lakes
  • Limits org to the same data warehouse
  • Slower query results
  • Can become a data dumping ground

Hacks to streamline and simplify

Leveraging modern tools and technology is the ultimate hack organizations can implement to streamline and simplify complex integration processes. The first way to do this is by eliminating manual coding. “Manual coding is tedious,” Wilmer says. “It’s prone to errors. It requires specialized skills. So you want to look for a modern platform that provides low/no code solutions.”

Low/no code solutions benefit entire organizations because they can be used by everyone, regardless of profession. These easy-to-use solutions empower staff to solve complex problems without relying on IT engineers to make sense of the data first.

“Everyone from tech-savvy engineers to business-savvy analysts needs to have access to data when and where they need it,” Wilmer stresses. “It should no longer be the bottleneck to business success.”

Stone agrees, adding that while he loves expressive development, code-centric integrations reduce the accessibility of the business rules that are codified into those integrations.

“Organizations reap tonnes of benefits by taking a visual, no/low code approach to integration,” Stone explains. “For one, it’s accessible to people with business knowledge. But also, customer after customer that I’ve worked with finds that it reduces the risk of management and maintenance of those integrations because they’re actually easier to hand off between team members.

“Integration is a clever way to solve a difficult, persistent problem,” he continues. “The combination of seeing how you can empower different skill sets to participate in the integration process and using a model-driven or visual way to create, support and maintain the integration is a powerful approach to solving any problem.”

Another way to simplify the complex is to focus on event-driven circumstances. Wilmer says there’s still a time and place for ‘bulk and batch’ processing, but an agile business needs real-time insights, which can only be achieved through streaming and API event-based data movement. “Modern applications need to be connected to share data,” he explains. “Event-driven data sharing powers enterprise automation.”

Beyond that, it’s important to scale with the cloud. “Obviously, when batch and high-volume process is necessary — and it will be — we want to scale with the cloud,” Wilmer adds. “Cloud computing has brought a seemingly limitless ability to reach peak performance and data processing.

“A data integration platform cannot be the bottleneck to achieving this agility. Look for a data platform that is born on the cloud and has the same ability to automatically scale with the cloud to maintain the desired performance.”

Finally, when it comes to simplification, think: consolidating integration. “It shouldn’t take four separate tools that specialise in only one or two methods of data integration to achieve business goals and objectives,” Wilmer insists. “Look for a complete integration platform that can do all four simultaneously to achieve integration, application integration, API management and governance.”

Winning with intelligent integration and automation

The enterprises that will win in the data economy are those that can harness data from every source and turn it into powerful insights. With data as the driving force of the future, it’s imperative to have an integration platform that can seamlessly integrate, automate and mobilize data to any data warehouse with a simple, powerful solution.

Successful integration leads to positive business outcomes and desirable user experiences. That’s why data-driven organizations integrate data to build a single source of truth. “This takes blending operational data with historical data, which involves data warehousing, capturing real-time data and streamlining data for analytics — all things that deliver immediate and tailored customer experiences,” Wilmer says.

“The more automated this becomes, the quicker you can achieve these outcomes. Enterprise automation drives efficiencies in technology, so you can deliver the goals and promises of your business.”

Stone adds, “Think of it this way, everyone always wants to eat the ice cream first. But you have to eat your broccoli first. Integration is like eating your broccoli to get strong and get those payoffs and benefits.”

SnapLogic is an intelligent integration platform that enables enterprise integration and automation. “With SnapLogic, you will accelerate the value of your data through ease of use and intelligent designs,” Wilmer says.

“SnapLogic simplifies your integration in the cloud by mobilizing the data and automating the processes that drive your business, enabling you to achieve enterprise integration and automation in a single platform — one that is purpose-built for the cloud and works with any cloud platform.”

Having that ability and the agility to pivot with technology and respond to challenges swiftly gives enterprises a leg up on the competition — competition that is scrambling to connect, reconfigure and rebuild their data integration processes.

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