Have you noticed your organization relying more and more on cloud-based software and platforms lately? Like most companies, yours probably uses dozens of SaaS applications, web services, and cloud data stores across departments.
The problem is, all that disjointed data floating around the cloud creates big headaches! IT spends countless hours manually transferring information between systems. Employees struggle to access reports with data trapped in organizational silos. And managers make decisions in the dark due to lack of visibility across systems.
These data fragmentation problems slow companies down at massive scale:
- 80% of IT budgets goes towards tedious point-to-point data integration tasks
- Employees waste over 30% of time hunting down needed data from cloud apps
- 57% of businesses cannot access real-time analytics due to data residing in isolated cloud platforms
But what if you could seamlessly stitch together all your cloud data sources – enabling real-time analytics, single-dashboard visibility, and automated data flows?
That’s exactly what cloud data integration solutions aim to provide. They act as the connective tissue between diverse cloud systems.
This guide will explore everything you need to know about cloud data integration. You’ll discover:
- Key benefits from connecting cloud data in one layer
- Common challenges to watch out for
- Use case examples across sales, marketing, operations
- A comparison of leading integration platforms
- Steps for evaluating and choosing a solution wisely
- Implementation best practices
So if you’re dealing with scattered cloud data slowing down your company, let’s jump in!
Why Integrate Your Cloud Data?
Integrating data from across cloud apps, databases, and services brings several compelling benefits:
1. Improved Accessibility
Rather than requiring employees to juggle logins across sales systems, marketing automation tools, support portals, and more – integrated cloud data means one-stop access. Teams save countless hours not having to manually export and import spreadsheets anymore. Integrations also facilitate self-service data exploration.
2. Enhanced Data Security
Surprisingly, some studies show properly integrated cloud data proves more secure in certain ways. The overall attack surface shrinks as you eliminate multiple access points guarded by lower security measures. Workflows also improve visibility into who is accessing data for governed usage. Leading solutions provide advanced encryption, data masking, and access controls.
3. Increased Efficiency Through Automation
Manual processes for moving data between cloud systems distract IT teams from more strategic initiatives. Automated scheduling and triggers enable machines to handle mundane data copying and transformations – saving thousands of work hours.
4. Scalability for Business Growth
As your operations grow, adding new cloud systems can get exponentially messy as each app needs to “talk” to every other one. A solid cloud integration platform with hundreds of pre-built connectors intermediates all these inter-relationships so you can painlessly scale to new tools.
5. Cost Savings
Cloud data integration solutions deliver hard cost reductions in three ways:
- IT software/hardware expenses drop by consolidating systems
- Hours spent on manual processes plummet thanks to automation
- Duplicate cloud subscription fees eliminated for apps replaced by integrated suite
Case studies report 20-35% cost savings on average from optimized cloud data usage. Those are hard numbers to ignore on the ROI calculations!
6. Superior Analytics and Reporting
Derived insights suffer when analysts need to manually compile reports from dozens of cloud sources in spreadsheets. Integration centralizes the data, enabling real-time dashboarding and analysis unimpeded by lagging replication schedules.
Now let’s explore some common obstacles with cloud application and data integration initiatives:
Key Challenges Around Integrating Cloud Data
While integrating data across cloud systems offers transformative value, you can also encounter bumps in the road if not careful:
1. Complexity of Migrating Legacy Systems
If your company used on-premise servers and legacy software systems, shifting historical data and workflows into the cloud proves exceptionally tricky. Watch out for these hazards:
- Exporting data without loss or corruption
- Reformatting legacy schemas/models for modern systems
- Freezing activity during cutover to prevent synchronization issues
- Meticulously testing accuracy of transformed datasets
- Retooling complex ETL processes for cloud platforms
Without robust migration utilities and careful data governance, projects fail Or drag on too long.
2. Managing Different Data Structures and Schemas
Every cloud software vendor defines data differently:
- JSON vs XML vs other formats
- 3rd party apps may utilize nonstandard schemas
- Plus custom fields, objects, and annotations configured uniquely for each company instance
Mapping all these schemas and reliably transforming data is no small feat. It requires specialized skills around hierarchical data handling and integration logic.
3. Security and Compliance Considerations
While integration offers security upside in consolidating apps, it also creates new privacy and compliance blindspots. Shuffling regulated medical records, personal customer data, or financial information between apps raises the stakes.
- Adding centralized platform increases attack surface vulnerable to malicious hacking
- More parties now access the unified data, increasing insider threat
- Persisting and mining regulated data could violate statutes
Organizations must force vendors to clarify responsibility around security controls and compliance readiness.
4. Choosing the Wrong Software
Myriad integration solutions promise quick connectivity between cloud apps. But legacy suites still focus mainly on complex on-premise environments. Others feature do-it-yourself toolkits lacking robust pre-built connectors, management UIs, or automation essentials for sustainable success.
5. Unpredictable Performance Degradation
The more apps and data flows connected, the more performance suffers from cascading dependencies. Slow data transfers or transformation failures infuriate employees. Rigorously baseline performance at peak workloads pre-deployment.
6. Lack of Standard Integration Protocols
No universal data schemas or APIs exist for integrating cloud platforms – unlike for legacy software. This requires more custom configuration and oils enterprise agility since tools don’t interoperate out-of-the-box.
Now that you understand both the potential benefits and common pitfalls around integrating data across cloud apps, let’s explore some actual use cases by department.
Cloud Data Integration Use Cases
Here are just a few examples of how leading organizations leverage centralized data from across key business systems:
1. Sales and CRM
Customer-facing teams gain access to integrated data from systems like Salesforce, Marketo, Zendesk, and niche SaaS apps. This powers superior visibility into pipeline health, campaign performance, and customer sentiment. SalesOps can track key conversion metrics across systems while reps resolve issues faster with consolidated client histories.
85% of B2B buyers choose vendors who demonstrate superior knowledge of their company and industry. Unified cloud data helps sales teams deliver that.2. Marketing
Fragmented data prevents digital marketing leaders from leveraging unified segmentation schemas, targeted messaging across channels, and attribution modeling. Centralized, trusted information from the Marketing Cloud, analytics tools, web apps, and other touchpoints drives more impactful campaigns.
60% higher conversion rates seen by B2C retailers with tightly integrated web, mobile, email, and social data.3. Finance
Disconnected systems stall key processes like financial planning, consolidation, regulatory reporting, and intercompany accounting. Shared data on the cloud integration platform smooths fiscal period close, budgeting, cash flow modeling, AP/AR, fixed assets, P&L, and variance analysis thanks to standardized inputs.
Global enterprises able to close books 20% faster after centralizing cloud financial data.4. Human Resources
Disjointed HR systems like Workday, SuccessFactors, Intuit Quickbooks, and niche apps hurt payroll, benefits management and compliance. Cloud data integration simplifies employee onboarding, core HR, compensation planning, talent development, and offboarding flows by connecting employee profiles, job data, compensation changes, trainings and other key info.
HR teams save 11 hours per new hire with integrated cloud data thanks to automated processes and paperwork.
5. IT and DevOps
Fragmented data siloes handicap IT leaders from ensuring robust service levels across cloud ops, business continuity, security, governance obligations and application development. Connectors which provide visibility into cloud monitoring, usage trends, code repositories, pipelines and release health allow technology teams to optimize architectures.
6. Transportation
Geospatial route data, fleet telematics, weather data, traffic sensors, IoT freight monitors and pricing feeds help transportation companies optimize driving routes, speed deliveries, improve safety, plot construction sites and more by ingesting myriad data sources.
7. Retail and eCommerce
Connecting inventory systems, online/in-store sales data, web traffic analytics, order fulfilment systems, and returns/exchange rates allows retailers to create consistent shopping experiences, optimize layouts, scale warehousing, and align supply chains.
The use cases are endless – but before diving into available data integration platforms, let’s lay out key assessment criteria for choosing the best one…
How To Select Your Cloud Data Integration Solution
With the market full of enticing options, use this scorecard to cut through the hype:
Data Sources Supported
How many out-of-the-box connectors and pre-built data adapters integrate popular cloud apps? Prioritize breadth here as you’ll likely subscribe to new systems over time.
Security and Compliance
Review encryption mechanisms, access controls, data activity logging, masking options and compliance certifications like HIPAA to confirm adequate protections for your industry’s data regulations.
Pricing Model
Calculate Total Cost of Ownership estimations based on license fees, data volume thresholds, support costs, required IT resources and professional services. Contrast perpetual licenses vs. subscriptions carefully across 3-5 years.
Performance Benchmarks
Analyze independent test results and customer-reported load volumes, transactions per second, and lag times – especially for data transformation and migration operations – to right-size capacity needs.
User Experience
Ease-of-use and flexibility considerations like intuitive dashboards, workflow automation options, availability of both code + no-code interfaces and quality of ongoing support vary widely between platforms.
Vendor Lock-in Risk
Migrating platforms later proves expensive if proprietary schemas, mismatched APIs and custom features lock you in early. Assess data portability concerns.
Built-in Analytics
Some solutions focus only on data movement – leaving dashboarding, reporting and analysis features up to separate BI tools. Prioritize all-in-one environments if those capabilities prove essential.
Now let’s evaluate ten leading options…
Top 10 Cloud Data Integration Platforms Compared
Managing data across assorted cloud applications presents big challenges and risks for IT teams. But choosing the right platform tailored to integrate your unique environment cost-effectively proves vital.
Here is an overview of ten top contenders:
1. Stitch Data
Best For: High-Scale Data Pipelines
Top cloud data pipeline platform enabling advanced users to move data from 90+ sources into data warehouses, lakes and databases. Favors code customization.
2. Alooma
Best For: AWS-Centric Organizations
Acquired by Google Cloud. Leading option still for AWS data transfers using REST APIs. Embeddable SDKs. Focuses just on data movement.
3. Jitterbit
Best For: Lightweight iPaaS + B2B Mediation
Lower-cost integration platform popular for B2B connectivity across legacy systems, SAP, supply chain apps and IoT. Reusable components.
4. Xplenty
Best For: Lean Data Transformation Libraries
Cloud data integration tool specializing in code-free SQL transformations, scheduling and job monitoring. Connect data easily between 150+ consumer apps and commercial platforms via 1,500+ connectors. Intuitive browser-based Experience lets anyone rapidly build data pipelines and analytics-ready datasets.
5. Apache Nifi
Best For: Open-Source Flexibility
Leading open-source Java tool for building automated data flows between disparate systems with easy drag-and-drop UI. IoT and machine connectivity focus. BYO cloud hosting.
6. elastic.io
Best For: iPaaS + Messaging Middleware
General-purpose integration platform-as-a-service delivers lightweight messaging middleware. Strong community support given open-source foundations.
7. Cleo
Best For: EDI + B2B Integration
Connects ERPs, supply chain software, retail systems and B2B exchanges. Specializes in EDI, FTP/SFTP, AS2 and ebXML translations for critical business integrations globally.
8. Workato
Best For: Integration Automation + Monitoring
Cloud automation platform gathers data from 130+ apps then uses triggers, stored procedures, schedules and gated flows to manage interconnected business logic. Robust monitoring.
9. Snaplogic
Best For: Big Data Scale + Advanced Analytics
High-volume data integration focused on big data use cases like IoT, data science and serverless apps. Flatter per-connection pricing. Partner ecosystem for AI/ML analysis.
10. Informatica
Best For: Large Enterprises Requiring On-Premise Support
Longtime integration leader covering all hybrid environments – both on-premises and multi-cloud backends. Very robust connectivity balanced by steeper learning curve.
This overview just skims the diverse capabilities targeting different integration needs. I encourage developing an RFI assessment matrix you can evaluate contenders against with weightings tailored to your key requirements determined above.
Allocating time for custom proof-of-concept testing with shortlisted vendors using actual company data also pays off.
Now let‘s wrap up with best practices to ensure your implementation succeeds…
Tips for Rolling Out Cloud Data Integration Smoothly
Approaching any complex IT project like integrating infrastructure across cloud applications using the leading practices below sets you up for maximum value with minimal headaches:
Start Small, Then Scale Out
Resist overwhelming your teams by connecting dozens of data sources initially. Crawl before running. Nail down adapters for just 1-2 critical systems, test thoroughly, then phase additional workflows quarter-by-quarter.
Clean Up Data First
Scrub all legacy application data through normalization, deduplication, transformation, and archiving routines before migration. Bad data will cascade issues downstream.
Create an Internal Collaboration Hub
Encourage teams to share integration ideas and report issues through an online portal or resource center. Capture tribal knowledge. Promote cross-departmental bonding between IT, sales, marketing, HR and finance partners.
Leverage Outside Expertise
Specialized cloud integration consultants and vendor professional services teams offer hardened blueprints, technical advisors and on-demand scaling to supplement internal Learning & Development. Budget for it upfront.
Start Automating Manual Tasks
Don‘t overthink early automation opportunities waiting for perfect solutions. Even basic triggers, file transfers, notifications and scripts eliminate tons of repetitive manual work. Let small wins build confidence.
Verify Security & Compliance
Confirm encryption, data access controls and activity audits align to corporate and regulatory policies protecting sensitive employee, customer, patient, partner or legislative data now co-mingled across integrated apps. Adjust configurations to close gaps.
Collaborate Across Departments
Driving adoption requires addressing multi-disciplinary feature requests and feedback to improve workflows for sales teams, store managers, clinicians and other business units. Align integration roadmaps to their pain points through sustained engagement.
Let‘s Connect!
And that wraps up our extensive overview discussing modern challenges around integrating distributed cloud data – along with the tangible benefits unified information delivers for velocity and scale when harnessed properly.
Hopefully the central takeaway illustrates how with so much organizational data and intelligence trapped within disconnected SaaS apps today, integration platforms represent prime tools for unlocking immense bottled-up value.
We covered example use cases demonstrating exactly how leading companies leverage integrated data from across sales systems, marketing technology stacks, finance tools and other critical software across departments to accelerate growth.
To recap, you discovered:
- 6 compelling reasons why integrating cloud data boosts efficiency
- 4 biggest implementation pitfalls to avoid
- Examples from healthcare transportation, retail sectors
- An expert comparison of 10 capable data integration platforms
- 8 best practices for launching new projects successfully
Now over to you! Does a fragmented cloud application ecosystem slow down your teams? Which data centralization use cases offer the biggest value: sales productivity or business insights?
Let me know if you have any other questions as you evaluate integration platforms for your cloud infrastructure and consider launching agilepilot programs. I‘m always happy to help advise. Just drop me a note below.
