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To a Hammer, Everything Looks Like a Nail To a digital hammer, everything looks like a data nail. AI is now part of every conversation. CIOs are being asked where AI fits, how fast it can be deployed, and what needs to happen first. But as with any new technology wave, not every problem is an AI problem. The organizations making the smartest progress aren’t forcing AI into everything—they’re identifying the places where it can genuinely improve operations, decision-making, or customer experience. In reality, most enterprises are still building the foundation: connecting their data, cleaning their systems, and evaluating the practical value of each AI project. That’s healthy. Good engineering starts with clarity, not speed. Where AI Makes a Real Impact AI is at its best when it helps people make better decisions or automates the work no one wants to do manually. Decision Support and Insight AI thrives when it has a wide range of connected data—on-prem, SaaS, cloud storage, warehouses, analytics platforms. With the right visibility, AI can help teams see both the big picture and the small details that matter. Predictive and Statistical Analysis Machine Learning (ML) models can detect patterns, highlight risks, forecast trends, and support preventative maintenance. These techniques have been reliable workhorses far longer than today’s Large Language Models (LLMs). Large-Scale Automation Reviewing thousands of customer records, analyzing transactions, or scanning for anomalies is not a good use of human hours. AI excels at that kind of scale. Fraud Detection AI is a powerful pattern-recognition tool. When implemented responsibly, it strengthens security and helps organizations react faster. Improving Product Experiences Subtle, smart features—like automated suggestions or guided fixes—often deliver more measurable value than flashy AI marketing language. LLMs vs. Algorithms LLMs generate text. They’re probabilistic systems, and they shine in areas like drafting, summarizing, and research. But consistency is not their strength. Behind every AI system is the infrastructure where algorithms and models run, each built for a different kind of precision. Deterministic algorithms, on the other hand, are predictable and repeatable. Loan decisions, pricing engines, logistics calculations—these still belong to rule-based systems built for precision. The real opportunity is knowing which tool fits the job, and combining them appropriately. LLMs vs. Machine Learning LLMs are for unstructured text. Machine Learning (ML) is for structured data and numerical analysis. If you need forecasts, patterns, or clean math, you rely on ML. If you need explanations, summaries, and natural-language interaction, you reach for LLMs. Most modern AI strategies require both. Start With the Need, Not the Tool Successful AI projects don’t begin with “We need AI.” They begin with questions like: What slows us down? Where are the bottlenecks? What decisions take too long? Where would automation free up meaningful time? Where would better data visibility improve outcomes? Modern enterprises succeed with AI when they choose projects grounded in real business problems, not hype. AI adds value when it solves a real operational problem. It stalls when it’s put in place for novelty. Personally, one of my favorite uses of AI is research. When a conversation hits a knowledge gap, I’ll ask ChatGPT for a high-level summary and source links. It gives me fast context. The difference is I verify what I read and use it as input—not as a replacement for judgment. Looking Ahead: Event-Driven Data, Edge Processing, and What’s Next for AI Readiness The future of AI will depend less on model size and more on how quickly and reliably data can move. Event-Driven Data Movement Systems are shifting from scheduled jobs to real-time triggers. When something happens—a customer update, a transaction, an alert—applications need to respond immediately. This is essential for real-time analytics and AI-assisted decision-making. Edge Processing With more data generated at the edge, not all of it needs to be shipped to a data center. Processing closer to the source improves performance, reduces cost, and increases resilience. Unified, AI-Ready Data Pipelines AI only works when the underlying pipelines work. Organizations need: Hybrid connectivity across all their systems Reliable replication and synchronization Predictable pricing (not per-GB surprises) Flexible storage options Automated governance and recovery This is where forward-looking data platforms earn their value: making sure data moves seamlessly, stays accurate, and is available when AI needs it. Setting Realistic Expectations AI is powerful, but it’s still a tool. The companies that win with it will be the ones that: Start with real needs Connect and trust their data Match the right technologies to the right problems Build systems that scale as their data grows We’ll continue sharing what we’re learning as AI and AI readiness best practices evolve and as organizations refine the systems and data management solutions that make it practical. Written by Rick Banister, CEO of Sesame Software, with Barry Polley, Data Scientist at Datafall Found this post helpful? Share it with your network using the links below.

In today’s digital world, managing data securely is not just a technical necessity — it’s a strategic priority. Every organization that handles sensitive or regulated information must navigate a complex landscape of laws, standards, and frameworks that govern how data is stored, accessed, and protected. These rules exist to build trust, reduce risk, and ensure accountability. But what does it truly mean to meet data security compliance? How do you take control of your data while satisfying regulatory requirements? In this article, we break down the essentials of data security compliance, provide actionable steps, and show how a modern data platform can help you stay ahead. Why Data Security Compliance Matters Compliance in data protection isn’t just a checkbox—it’s foundational to how an organization operates. Frameworks like GDPR, HIPAA, CCPA, and SOC 2 define rules for handling personal and sensitive data. Failing to comply can lead to financial penalties, legal liabilities, and reputational harm. When done right, pursuing data security compliance offers real advantages: It strengthens customer trust by demonstrating that privacy and protection are taken seriously. It helps prevent breaches through disciplined security measures. It enforces consistent data governance and clearer policies. It differentiates your organization in the market as a trusted steward of data. Taking control of your data means embedding compliance into your systems—not treating it as an afterthought. Key Elements of Data Security Compliance To build a robust program, focus on these core areas: Data Inventory & Classification Know what data you hold, where it lives, and how sensitive it is. Classify data into levels (e.g., public, internal, confidential, restricted) to guide protections. Access Controls & Authentication Use role-based access (RBAC) to limit permissions. Enforce multi-factor authentication (MFA) for additional security. Encryption In Transit & At Rest Encrypt datasets both during transmission and while stored—a vital layer of defense against unauthorized access. Auditing & Monitoring Perform regular security audits, monitor systems continuously, and log activity for traceability. Incident Response Planning Prepare a detailed breach response strategy that includes detection, containment, notification, and recovery steps. Training & Awareness Educate employees on best practices, phishing risks, and data handling policies—human error is often a weak link. Vendor & Ecosystem Compliance Ensure partners, vendors, and connected systems abide by your data security compliance standards. Include requirements in contracts and perform periodic assessments. By covering these areas, you build a compliance framework that supports both security and business objectives. Practical Steps to Make Data Security Compliance Work Here’s how to translate principles into action: Conduct a Data Protection Impact Assessment (DPIA) to identify risk areas and plan mitigations. Draft clear, understandable data protection policies that everyone can follow. Automate compliance tasks (classification, monitoring, reporting) using a capable platform. Regularly update security controls to counter evolving threats. Secure leadership support to allocate resources and drive cultural change. Document all compliance activities, audits, and decisions—this record is vital for audits. Communicate transparently with employees, customers, and stakeholders about your compliance efforts. Why Simplicity Matters in Data Security Compliance Managing data security compliance can feel complex—but your tools shouldn’t add friction. You need platforms that are powerful, but also straightforward enough for daily use. At Sesame Software , our goal is to simplify compliance by offering: Centralized replication and backup across systems. Automated workflows for retention policies, auditing, and reporting. Real-time monitoring and alerting for anomalous activity. Intuitive interfaces that empower both IT and compliance teams. Flexibility to support different deployment models and data residency requirements. With this balance of capability and usability, compliance becomes part of your data management foundation—not a burdensome overlay. Moving Forward with Confidence Achieving data security compliance is an ongoing journey, not a one-time fix. Regulations evolve, threats adapt, and technology shifts. But with the right mindset, processes, and platform, you can stay ahead. Remember: compliance is more than avoiding fines. It’s about building trust, ensuring resiliency, and enabling confident growth. Start now by assessing your current posture, identifying gaps, and putting in place those key elements. Over time, a mature approach to data security compliance will become a competitive advantage. Protect your most valuable asset—your data. Manage it smartly. Comply with confidence. Next Steps to Keeping Control of Your Data Take the next step toward stronger data security compliance with Sesame Software: Explore our platform: See how our replication and backup capabilities simplify compliance and data protection. Match your architecture: Learn which connectors best support your existing systems and scale requirements. Book a demo: Validate your architecture with a live walkthrough from our data experts. Download our compliance checklist: Quickly evaluate your organization’s readiness and identify areas for improvement. Data Security Compliance and Sesame Software FAQ How does Sesame Software support data security compliance? Our platform automates replication, backup, and monitoring processes to ensure your data remains consistent, auditable, and protected. These capabilities support compliance with frameworks such as GDPR, HIPAA, CCPA, and SOC 2. Can Sesame Software help with audit readiness? Yes. By maintaining synchronized, timestamped copies of your data, Sesame Software provides the visibility and traceability auditors require—reducing the effort needed to demonstrate compliance. What makes Sesame Software different from other data management tools? Sesame Software combines simplicity with enterprise-grade power. We deliver near real-time replication, flexible storage options, and built-in reliability so your team can focus on strategy, not manual compliance tasks. Found this post helpful? Share it with your network using the links below.

If your team is exploring how to bring AI into your enterprise workflows, you’ve probably hit a familiar challenge: the data isn’t ready. It’s trapped in siloed systems, inconsistent across platforms, or missing altogether. And while plenty of vendors will offer to “start fresh,” building a new data foundation from scratch is time-consuming, expensive, and often unnecessary. Here’s the good news: you may already have what you need if you can access, move, and prepare your data properly. Why Data Readiness Is the First Step in AI Success No matter how advanced the model, AI is only as powerful as the data you feed it. That means: Incomplete records = incomplete predictions Dirty data = misleading insights Inaccessible systems = missed opportunities Before building models or integrating with AI platforms, organizations need a reliable way to centralize and structure their data without months of rework or risky migrations. The AI Problem You Can’t Solve With a Model Many teams try to push forward with AI while hoping their fragmented systems “catch up.” But without a scalable way to move and sync data between systems, even the best AI projects fall short. Common issues include: Disconnected cloud and on-prem systems Manual data exports and inconsistent file formats Delays in syncing real-time data Redundant or incomplete datasets feeding downstream tools And perhaps most frustrating: AI tools only work if they can actually access the data. How Sesame Software Helps You Get AI-Ready At Sesame Software, we help you unlock your existing data so you can put it to work faster. Instead of starting from scratch, our platform helps you: ✅ Replicate and sync data across cloud and on-prem platforms ✅ Prepare clean, structured datasets for tools like IBM watsonx and other AI/ML frameworks ✅ Automate data pipelines so your models are powered by fresh, reliable inputs ✅ Avoid manual exports and brittle connections that slow down progress With no-code setup, support for Salesforce, NetSuite, MySQL, and more, and flexible deployment options, we make it easy to feed your AI tools without rebuilding your architecture. Real Results, Not Just Hype We’ve helped enterprise teams accelerate their AI readiness by months just by improving how they access and move the data they already had. That means less time wrangling spreadsheets and more time training, testing, and generating results. The Bottom Line If AI is on your roadmap, your data strategy has to come first. But that doesn’t mean ripping out systems or building new infrastructure. With the right tools, you can prep and power your AI initiatives using the systems you already trust. Ready to make your data AI-ready – without starting from scratch? Book a demo today and see how Sesame Software gives your teams full control of your data for wherever the future is moving you.

It’s been three years since ChatGPT’s public debut. This milestone seemed to bring the Turing Test within reach. Yet, rather than fearing a Skynet-style future, many of us are grappling with a more mundane problem: what exactly to do with this new toolset. Ironically, it’s often easier to tell whether you’re talking to a robot than to know if the person (or bot) on the other end is human. Personally, if the response is written in flawless Harvard-level English, I suspect it isn’t. Chat interfaces, however, are only one manifestation of AI. In a corporate context, unless they’re connected to a company’s data, their advice is often limited. As for website chatbots? I want to drive a stake through every one I’ve ever encountered. Human support staff can be disappointing at times, but chatbots manage to drive me nuts all the time. The first wave of AI projects has produced both winners and losers, as is typical with any new technology. The real challenge is that most companies still don’t know why they should use AI in the first place. End users are looking for ROI that still feels elusive, while AI vendors are wondering where the paying customers are. We see staggering valuations for AI companies. However, often the value is driven by vendor-to-vendor activity rather than actual customer demand. OpenAI’s use of Oracle Cloud Infrastructure, for example, boosted Oracle’s stock price. Other firms build on OpenAI or Grok. At some point, these giants will need more than partnerships and infrastructure—they’ll need real, paying customers. AI Adoption Challenges: From Hype to Practical ROI I started attending AI-themed trade shows in 2023. The vendors were often impressively prepared, with slick booths and bold promises to “solve all your AI problems.” But the potential customers? Many came without a clear agenda. Few had specific projects or problems in mind. They were curious to see what AI could do for them. Some came to sell consulting services. Others hoped to find ways to bring AI into their companies—often without any defined requirements. The idea of “using AI everywhere” became fashionable in some circles. However, it was both brave and, frankly, foolish. Companies were being encouraged to spend on AI “just in case” they might find a problem worth solving later. A Solution Looking for Problems If you start with a shiny new tool and then go hunting for problems to solve, you’re likely to be searching for a long time. Companies have real challenges—doing things smarter, faster, or cheaper. AI does have strong use cases: drafting customer communications, predicting revenue, automating repetitive tasks, and even performing research that would otherwise take days. But as long as organizations approach AI as a hammer looking for nails, they’ll face resistance. After all, many jobs depend on not automating certain tasks out of existence. One of my personal favorite uses of AI is research. When a conversation hits a dead end because neither person knows enough about a topic, I ask ChatGPT. In seconds, I get a solid, college-level overview—often with links to original sources. I trust it because I understand its limitations and verify the references. That’s far better than asking someone to speculate from a position of ignorance—something both humans and AI tend to do when cornered. Setting Realistic Expectations for AI Projects The real question is how to set expectations and focus on AI projects that deliver tangible results. That’s the subject of my next article: “ How to Identify AI Project Candidates in the Modern Enterprise. ” Future pieces in this series will focus on practical corporate needs—specifically, how AI can be applied to improve decision-making and deliver measurable ROI. Next Steps to Take Control of Your Data Sesame Software's data pipelines ensure information flows cleanly and consistently across systems. This provides the quality, structure, and governance AI tools need to deliver trustworthy insights. Talk to a Data Expert about building the data foundation that makes AI practical, measurable, and ROI-driven. FAQ: Data Readiness for AI Why is data readiness the first step toward effective AI? AI can only be as accurate as the data it’s built on. If your data is incomplete, inconsistent, or siloed, AI results will be unreliable. Sesame Software’s data pipelines ensure data is clean, connected, and governed—so AI tools can operate on trusted information instead of guesswork. How does Sesame Software help companies prepare for AI? Our platform streamlines data replication and integration across every environment—on-prem or cloud—creating a unified source of truth. This consistency gives organizations the reliable foundation needed for analytics, automation, and AI-driven insights. What’s the biggest barrier to AI success in most enterprises? Most AI projects stall not because of the models, but because the underlying data isn’t ready. Disconnected systems, manual data movement, and lack of governance make it impossible to scale AI with confidence. Sesame Software eliminates these barriers by keeping data synchronized and audit-ready. How can I tell if my organization is AI-ready? You’re ready when your data is unified, up to date, and governed—when insights can be trusted without constant manual cleanup. If achieving that feels out of reach, data readiness through automated pipelines is the right place to start. Found this post helpful? Share it with your network using the links below.

SANTA CLARA, CA — [Nov 3, 2025] — As data protection costs continue to rise across the enterprise software landscape, Sesame Software stands apart with a commitment to stable, predictable pricing for its Salesforce Backup and Recovery solution. While many vendors have increased rates and introduced tier-based limits, Sesame Software continues to provide enterprise-grade protection with flat annual pricing and unlimited data movement, ensuring customers can scale without surprises. “Data protection should deliver peace of mind, not budget uncertainty,” said Rick Banister, CEO of Sesame Software. “Our customers deserve a reliable solution that won’t penalize them for growth. That’s why we’ve maintained the same straightforward pricing model — no per-GB charges, no hidden fees, and no sudden increases.” Protect your Salesforce data with near real-time replication and predictable, flat-rate pricing. Sesame Software’s Backup and Recovery for Salesforce empowers organizations to safeguard their mission-critical data with near real-time replication, granular restore options, and SOC 2 Type II–certified security. Its hybrid deployment model allows enterprises to choose where data resides — on-premises, in their private cloud, or a hybrid combination — giving IT teams full control over compliance and recovery processes. In an era where most vendors are locking key functionality behind premium tiers, Sesame Software continues to prioritize accessibility and performance for all customers. The platform’s no-code interface, automated replication, and comprehensive restore capabilities make it both easy to use and powerful enough for large-scale environments. “Our goal has always been to make enterprise data management simple, scalable, and affordable,” added Banister. “We’re proud to deliver a platform that helps organizations maintain control — both of their data and their costs.” Looking ahead, Sesame Software will soon extend its trusted technology to a SaaS-based offering, providing the same reliable features and transparent pricing through a fully managed, cloud-native platform. About Sesame Software Sesame Software provides enterprise data replication and export solutions that help organizations take control of their data. View this release on PR Newswire. About Sesame Software's Salesforce Backup and Recovery Sesame Software’s Salesforce Backup and Recovery solution gives enterprises complete control over their Salesforce data — without the hidden costs or complexity common in other platforms. With near real-time replication, granular restore capabilities, and flat annual pricing, organizations can safeguard mission-critical Salesforce data while maintaining full visibility and compliance across their environment. Built for scale, performance, and simplicity, the solution ensures fast, reliable recovery from any incident — whether it’s accidental deletion, integration errors, or corruption. Engineered with SOC 2 Type II–certified security and flexible deployment options, Sesame Software lets customers decide where their data resides — on-premises, in their private cloud, or a hybrid configuration — ensuring compliance and confidence at every step. Soon, this trusted protection will also be available as a fully managed SaaS offering, bringing the same proven features, transparent pricing, and control to a streamlined, cloud-native experience.

Subscription Businesses Run on Data The subscription economy continues to outpace traditional business models, reshaping industries from software to consumer goods. Unlike one-time sales, recurring revenue depends on constant customer engagement, retention, and accurate forecasting. For companies built on subscriptions, data is no longer a back-office function, it is the fuel for survival and growth. But managing this data isn’t simple. Customer interactions often live in Salesforce, while billing, revenue recognition, and compliance reporting are handled in NetSuite. Without tight integration between the two, businesses risk creating silos that slow down insights, delay financial reporting, and leave churn risks hidden until it’s too late. The Churn Challenge Churn is the subscription economy’s biggest enemy. Even small percentages of customer loss compound quickly when revenue is recurring. The ability to spot early warning signs — declining engagement, missed payments, support escalations — can make the difference between steady growth and stagnant MRR. That requires unified, reliable data. If Salesforce and NetSuite operate in isolation, sales teams may not see financial red flags, while finance teams may lack visibility into customer sentiment. The result is an incomplete picture of customer health, and missed opportunities to intervene. Why Integration Matters Power growth with unified Salesforce + NetSuite data. Seamless integration between Salesforce and NetSuite closes this gap. When data flows in near real time between the two platforms, subscription businesses gain a single view of the customer that spans the entire lifecycle, from lead to renewal. Sales sees subscription history and payment trends without leaving Salesforce. Finance gains accurate forecasting powered by live pipeline data. Leadership has cross-system visibility into churn risk, customer lifetime value, and recurring revenue trends. This is where modern data pipelines stand apart from brittle point-to-point integrations. By replicating and synchronizing data across systems, companies get not only connectivity but also reliability, flexibility, and the ability to scale as data volumes grow. The Sesame Software Advantage Sesame Software was built to solve exactly this challenge. Our platform provides near real-time replication between Salesforce, NetSuite, and the destinations of your choice , whether that’s a cloud data warehouse, on-prem database, or data lake. For subscription businesses, this means: No blind spots between CRM and ERP Cleaner, normalized data ready for analytics and AI models Audit-ready backups for compliance and revenue recognition Flexibility to expand pipelines as new data sources come online Because Sesame Software isn’t locked into a single storage ecosystem, you also avoid the vendor lock-in that often drives up costs over time. Data can be stored where it makes the most sense — in the cloud, on-prem, or a hybrid approach. Future-Proofing the Subscription Economy As the subscription economy matures, data strategies must keep pace. Companies that succeed will be the ones that treat data as a first-class asset, not an afterthought. Seamless Salesforce + NetSuite integration is no longer optional, it’s the foundation for reducing churn, improving customer experiences, and growing recurring revenue streams. The future of data management in the subscription economy is clear: flexibility, visibility, and speed.  Businesses that invest in these capabilities today will be best positioned to thrive tomorrow. Next Steps See our full range of NetSuite and Salesforce solutions to unlock real-time insights. See how Sesame Software powers near real-time data replication  to keep your CRM, ERP, and analytics perfectly in sync. Talk to a Data Expert  about building a unified data strategy that drives renewals, visibility, and growth. Salesforce + NetSuite Integration FAQ What makes replication more reliable than traditional integration methods? Traditional integrations often move data only when triggered by specific events or schedules, creating gaps and potential data loss. Sesame Software uses automated replication that maintains a dedicated, continuously updated copy of your data. This ensures consistent performance at scale, even as data volumes grow or systems evolve — providing both reliability and flexibility for analytics and reporting. How does Sesame Software ensure Salesforce and NetSuite stay aligned? Sesame Software continuously replicates data between Salesforce and NetSuite instead of relying on point-to-point integrations. This approach keeps customer, billing, and revenue records synchronized in near real time, eliminating version mismatches and reducing the need for manual updates or reconciliation. Found this post helpful? Share it with your network using the links below.

Enterprises now manage more data than ever. This data is scattered across various apps, databases, and clouds. Traditional ETL workflows are often rigid, slow to change, and costly to maintain. Composable data pipelines offer a different path. They break data movement into small, reusable functions that you can combine, test, and scale as needs evolve. The result is faster time to value, cleaner data for analytics and AI, and greater control over where your information lives. At Sesame Software, we build pipelines with modular components that do one job well. Producers pull data from sources like Salesforce or NetSuite. Transformers normalize, enrich, or redact fields. Consumers write data to warehouses, object stores, or analytics tools. Because each function is independent, teams can prototype quickly, add custom logic, and scale without reworking the whole pipeline. Why Composable Data Pipelines Matter Now Business leaders want results fast. Composable data pipelines let you spin up proof of concepts and production flows without rewriting large jobs. When a new use case appears, you can reuse existing functions and add only what’s necessary. This approach lowers risk and shortens delivery cycles. Scaling is another significant advantage. Modern architectures rely on serverless and distributed compute to process high volumes without huge infrastructure overhead. With a modular approach, you can scale individual pipeline stages independently. This is more cost-efficient and easier to monitor. Compliance and data quality matter more than ever. Pipelines can include validation, normalization, enrichment, and PII redaction steps before any dataset reaches analytics or archives. This makes audits simpler and reduces exposure. Finally, AI readiness depends on clean, tagged, and consistent data. Composable pipelines automate wrangling, add metadata, and produce reliable training sets that improve model performance. How Composable Data Pipelines Work Our model separates responsibilities into small, pluggable pieces. Producers connect to sources such as Salesforce, NetSuite, JDBC, or third-party APIs. Reusable functions perform transformations: normalize data types, add metadata tags, remove unnecessary fields, enrich addresses, or redact sensitive values. Consumers persist results to Snowflake , S3 , SQL databases , or BI tools. Because each step is auditable and independent, you get clearer lineage and easier troubleshooting. You can substitute or update a single function without affecting the rest of the flow. This also lets teams version functions and test changes safely. Prebuilt vs Custom Functions for Composable Data Pipelines Sesame provides prebuilt functions for common tasks like string normalization, default values, and PII handling so you can move quickly. For advanced needs, you can add custom functions for AI enrichment, third-party API calls, or serverless scaling using AWS Lambda or equivalent. Mix and match prebuilt and custom functions to create pipelines tailored to your architecture. Start with low-risk, high-value flows (for example, Salesforce → Snowflake) and iterate toward richer enrichment and governance over time. Business Benefits of Composable Data Pipelines Faster proofs of concept and lower time to value. Improved data quality and audit readiness. Elastic scale without oversized infrastructure. Easier maintenance and faster feature delivery. Better datasets for analytics and machine learning. These translate to faster insights, lower operational costs, and a stronger compliance posture. Data pipelines should be flexible, auditable, and ready for what comes next. Sesame Software’s composable data pipelines help you move, clean, and govern data in near real-time. This ensures analytics and AI teams get trustworthy inputs while engineering teams benefit from simpler, safer flows. If you want a quick checklist or a short demo, click the button below. Next Steps See our full range of pipeline capabilities to design modular, auditable data flows. Learn which connectors match your architecture and scale needs. Book a demo to validate your architecture and prioritize a pilot. Download a quick evaluation checklist to share with your team. Composable Data Pipeline FAQ What are composable data pipelines? Composable data pipelines use small, reusable functions (producers, transformers, consumers) that connect to form end-to-end flows. They replace monolithic ETL with modular parts you can reconfigure for new use cases. How do composable data pipelines differ from traditional ETL? Traditional ETL is typically a single, rigid process. Composable pipelines are modular, easier to test, and faster to change — which reduces time-to-value for POCs and improves maintainability. Are composable pipelines secure and compliant? Yes. Functions can include built-in normalization, redaction, and metadata tagging so sensitive fields are handled before data reaches analytics or archives. Sesame supports GDPR/HIPAA controls and audit logs. How long does it take to implement a composable pipeline? Times vary by use case. A simple replication pipeline (e.g., Salesforce → Snowflake) can be configured in days; advanced enrichment or custom functions can take a few weeks. We help prioritize quick wins first. Can composable pipelines prepare data for AI? Absolutely. Automated wrangling, metadata tagging, and consistent formatting create high-quality training datasets for ML models. Found this post helpful? Share it with your network using the links below.

SANTA CLARA, Calif., Oct. 15, 2025 /PRNewswire/ — Sesame Software and DataNovata announced a collaboration delivering an end-to-end solution to a common problem: historical NetSuite data is costly and difficult to access for reporting, audits, and eDiscovery because maintaining live NetSuite access requires expensive licenses and fragile, time-consuming workflows. The combined offering exports and preserves NetSuite records while providing a searchable, NetSuite-like read-only user interface so teams regain fast, auditable access to historical records without ongoing NetSuite licensing. Sesame Software performs full and incremental NetSuite exports that preserve transactional records, metadata, and relational structure and provides flexible endpoints to databases or cloud object stores. Built for scale, the export process minimizes system impact and keeps archived data compliant and under customer control. Incremental exports keep archives current without disrupting production systems, and configurable endpoints to S3 or cloud databases let organizations choose storage patterns for operations and retention. Export full-fidelity NetSuite data with Sesame Software, then view, search, and report on it with DataNovata’s NetSuite-like web UI — secure, read-only access that keeps you in control. DataNovata analyzes the exported schema and generates a secure HTML5 web UI that mirrors NetSuite relationships while preventing modification through read-only access. Business users, auditors, and IT teams can search, report, and visualize historical NetSuite data in a familiar interface without touching live instances. Typical use cases include month-end reporting, regulatory audits, legal eDiscovery, and historical analytics. The solution supports role-based access control, encryption at rest and in transit, and audit logs to satisfy internal and external compliance requirements. Customers can deploy the workflow in weeks. The combined solution integrates quickly into existing environments and requires minimal training. Finance, compliance, and operations teams gain immediate visibility into historical records and the ability to run reports without the friction of live NetSuite access. “DataNovata has worked ideally with Sesame Software’s NetSuite data extracts to help customers incorporate reporting customizations in their NetSuite implementations. We welcome our ongoing collaboration with the Sesame Software team,” said Jon Sherrington, SVP, DataNovata Ltd. About DataNovata DataNovata transforms exported application databases into secure, searchable web applications for reporting and archival access. The company’s tools simplify schema analysis and create a NetSuite-like read-only experience for business users, auditors, and IT teams. About Sesame Software Sesame Software provides enterprise data replication and export solutions that help organizations take control of their data. View this release on PR Newswire. About NetSuite Data Archive Sesame Software’s NetSuite Data Archive solution enables businesses to securely export and preserve their complete NetSuite dataset—including transactional records, metadata, and relationships—while maintaining full audit and reporting capability even after offboarding from NetSuite. This ensures compliance, accessibility, and peace of mind, giving organizations lasting visibility into their financial and operational history without relying on costly NetSuite licenses. A common use case for the NetSuite Data Archive is supporting audit readiness and business continuity after a system migration. Companies often leverage it to retain access to years of financial transactions, customer data, and historical reports while transitioning to a new ERP or reducing license costs. With archived data structured for easy retrieval and compatible with analytical tools, teams can continue reporting and analysis seamlessly, long after their live NetSuite instance is closed.

For many organizations, NetSuite is the backbone of financial and operational data. But reporting often lags behind business needs. Manual exports, spreadsheet reconciliations, and long waits for insights leave teams working with yesterday’s numbers instead of today’s reality. By the time reports are ready, the moment to act has often passed. The Problem with Delayed Reporting In today’s fast-moving market, slow reporting creates costly setbacks: Missed opportunities  when shifts in demand or performance aren’t visible fast enough. Bottlenecks  as finance and operations teams chase down spreadsheets. Compliance risks  when reporting data is incomplete, outdated, or inconsistent. When decisions depend on lagging reports, organizations lose both agility and accuracy. Real-time analytics is no longer a luxury, it’s a necessity. Why Real-Time Analytics Matters Real-time analytics transforms NetSuite from a system of record into a live engine for insights. With always-current data: Executives view dashboards built on today’s numbers, not last week’s. Finance teams reconcile faster with fewer errors. Analysts focus on strategy instead of wrangling exports. In short, real-time analytics shifts teams from reactive reporting to proactive decision-making. How Sesame Software Helps Near Real-Time NetSuite Analytics Sesame Software eliminates reporting delays with near real-time replication of NetSuite data  into the analytics platform or data warehouse of your choice. Our pipelines are designed for scale and reliability, so your team can: Streamline reporting workflows  by automating exports. Centralize data across systems  for a single, trusted source. Empower decision-makers  with accurate insights at the moment they’re needed. Whether you rely on Snowflake , Redshift , BigQuery , or another warehouse, Sesame Software ensures your NetSuite data is always up to date and analytics-ready. If NetSuite is your system of record, don’t let outdated exports and spreadsheets hold you back. Real-time analytics is no longer a luxury - it’s a competitive necessity. Next Steps See our full range of NetSuite solutions to unlock real-time insights. Explore our NetSuite Export solution  for fast, accurate replication. Talk to a Data Expert  about building a real-time reporting strategy tailored to your business. Near Real-Time NetSuite Analytics FAQ Can NetSuite do real-time reporting on its own? NetSuite includes built-in reporting tools, but most reporting relies on batch exports or saved searches. These often introduce delays. For truly real-time analytics, data must be replicated into a warehouse or BI platform. What are the drawbacks of manual NetSuite exports? Manual exports create bottlenecks, increase the risk of errors, and leave teams working with outdated numbers. They also slow down reconciliation and decision-making. How does Sesame Software enable real-time NetSuite analytics? Sesame Software replicates NetSuite data in near real time into your chosen data warehouse (such as Snowflake, Redshift, or BigQuery). This ensures executives, finance teams, and analysts always work from current data. Which platforms can NetSuite data replicate into? Sesame Software supports leading cloud warehouses and BI platforms including Snowflake, Amazon Redshift, Google BigQuery, and others. This gives organizations flexibility in where they run analytics. Why is real-time analytics a competitive advantage? With live access to NetSuite data, organizations can act on insights faster—whether it’s spotting market shifts, improving financial visibility, or staying compliant. Faster decisions mean a stronger competitive position. Found this post helpful? Share it with your network using the links below.

Data-driven businesses rely on two major database structures: relational databases  for transactions and columnar databases  for analytics. Each has unique strengths—and limitations. The relational vs columnar database challenge? Most organizations need both. That’s where Sesame Software  comes in. Our platform seamlessly moves data across both structures, ensuring speed, accuracy, and scalability without compromise. What is a Relational Database? Relational databases (RDBMS) organize data into tables with rows and columns. They’re ideal for transactional processing  and structured queries. Popular platforms include MySQL, PostgreSQL, Oracle, and SQL Server . Key advantages: Data integrity : Built on ACID principles (Atomicity, Consistency, Isolation, Durability). Complex joins : Handle relationships between data points. Consistency : Reliable for day-to-day transactions. Challenges: Performance overhead : Joins across large tables slow queries. Rigid structures : Requires normalized data, limiting flexibility. Scalability limits : Struggles under massive data volumes. Why Columnar Databases Are Different Columnar databases store information by column rather than row , making them powerful for analytics and reporting. Examples include Amazon Redshift , Snowflake , Google BigQuery , and Vertica . Key advantages: Faster analytics : Query only needed columns, cutting I/O. Compression : More efficient storage saves costs. BI-ready : Perfect for dashboards, aggregations, and trend analysis. Challenges: Poor fit for transactions : Updating single rows is slow. Not real-time : Better for batch analysis than live operations. Why Most Businesses Need Both Relational databases  keep your operations running smoothly. Columnar databases  deliver insights at scale.Together, they provide the complete picture of your business . But moving data between them isn’t easy. That’s where Sesame Software helps. How Sesame Software Simplifies Data Movement Our platform automates replication between relational and columnar databases with built-in optimization: Data Chunking : Breaks large sets into manageable pieces to avoid deadlocks. Incremental Updates : Replicates only new or changed records for efficiency. Intelligent Checkpointing : Resumes from the last successful point if transfers fail. Cross-platform compatibility : Works with leading RDBMS and columnar systems. Result:  Faster pipelines , fewer failures, and always up-to-date insights. Whether your data lives in Salesforce, NetSuite, Oracle, Redshift, BigQuery, or Snowflake , Sesame Software ensures secure, near real-time movement. Next Steps Discover why our ETL approach beats traditional methods. Explore our connectors   for Salesforce, NetSuite, Oracle, Redshift, BigQuery, and more. Talk to a Data Expert  to map the right pipeline for your data. Relational vs Columnar Database Comparison FAQ What’s the difference between relational and columnar databases? Relational databases store data in rows for transactions. Columnar databases store data in columns for fast analytics. Why would a business need both? Transactional systems require relational databases, while analytics and BI depend on columnar structures. Together they provide a full operational + analytical view. How does Sesame Software handle both? By replicating data between relational and columnar databases with chunking, incremental loads, and checkpointing to ensure performance and reliability. Which platforms are supported? Popular relational (MySQL, Oracle, SQL Server, PostgreSQL) and columnar (Redshift, Snowflake, BigQuery, Vertica). Found this post helpful? Share it with your network using the links below.

In today’s digital economy, data is the backbone of every business decision . NetSuite, as a leading ERP solution, helps organizations centralize operations, but the value of that data depends on one thing: quality . Without accurate, consistent, and timely data, reports are skewed, customer experiences suffer, and growth opportunities slip away. Ensuring NetSuite data quality is not optional — it’s a foundation for success. NetSuite data quality ensures records are accurate, validated, and current. How Poor Data Quality Hurts Business 1. Decision-making risks Basing strategies on incomplete or inaccurate data leads to wasted resources and missed opportunities. Example: targeting the wrong audience due to flawed sales records. 2. Reporting inaccuracies Bad data skews KPIs and financial metrics, creating false forecasts. Correcting errors delays reporting cycles and drains resources. 3. Operational inefficiencies Errors in transactions, workflows, and customer details disrupt processes. Inaccurate inventory may cause stockouts or overstocking—hurting both customer satisfaction and profitability. Ensuring Data Quality in NetSuite 1. Regular Data Cleansing Remove duplicates, fix inconsistencies, and standardize formats to keep data accurate and usable. 2. Validation Rules Prevent bad data at entry by enforcing correct formats (e.g., emails, phone numbers). 3. Consistency Across Teams Use standardized formats and a data dictionary  to keep definitions aligned. 4. Data Governance Framework Define roles, responsibilities, and policies to ensure uniform handling of data. 5. Automation & Tools Automated processes speed up cleansing, validation, and monitoring—reducing human error and freeing teams to focus on strategy. How Sesame Software Helps Improve NetSuite Data Quality At Sesame Software , we specialize in data management for NetSuite and other enterprise systems. Our solution helps you: Replicate NetSuite data  with complete fidelity, including child tables and attachments. Cleanse and validate  data automatically to maintain integrity. Standardize across systems  so every department works from a single version of truth. Enable near real-time access  to accurate data for reporting and analytics. With Sesame Software, you can ensure that your NetSuite environment is always running on reliable, accurate data —so reports, decisions, and operations stay on track. Next Steps Explore our NetSuite Export solution  for fast, accurate replication. Learn how we export your NetSuite data with full fidelity. Talk to a Data Expert  about building a NetSuite data quality strategy. Read our collection of blog articles with info, tips, and tricks regarding NetSuite and our solutions to help maximize your investment. NetSuite Data Quality FAQ What is data quality in NetSuite? Data quality means ensuring NetSuite data is accurate, complete, consistent, and up to date. Why is poor data quality a problem? It leads to misinformed decisions, incorrect reports, operational inefficiencies, and wasted resources. How can businesses improve data quality in NetSuite? By cleansing data, setting validation rules, enforcing governance, and using automation tools. How does Sesame Software help with NetSuite data quality? Sesame Software replicates NetSuite data accurately, enforces consistency across systems, and supports automation to keep data clean. Found this post helpful? Share it with your network using the links below.

The latest NetSuite outage last month affected NetSuite users across multiple locations. NetSuite is a popular cloud-based ERP (Enterprise Resource Planning) software used by many businesses for their financial and operational management. The outage caused widespread disruption, preventing businesses from accessing critical data and applications, such as financial reports, customer information, and inventory management systems. The impact of the outage was felt by businesses of all sizes, from small startups to large enterprises. In some cases, businesses were forced to halt operations entirely, leading to lost revenue and productivity. The outage also caused significant frustration for users who rely on NetSuite’s services for their day-to-day operations. Customers took to social media to express their dissatisfaction, highlighting the importance of backup plans and redundancy measures. The NetSuite outage serves as a reminder of the importance of having a backup plan in place for critical business systems. Companies that rely on cloud-based software should have redundancy measures in place to ensure that they can continue operations in the event of an outage. This can include having backup servers, data centers, or even alternate software solutions that can be used as a temporary backup until the issue is resolved. Sesame Software can serve as a reliable backup plan in case of a NetSuite outage. If your business heavily relies on NetSuite for its daily operations, any downtime or disruption can have severe consequences. With Sesame Software, you can easily backup your NetSuite data to a secure location, ensuring that your data remains accessible even during a NetSuite outage. This not only helps mitigate any potential losses but also ensures that your business can continue to function without any major disruptions. Overall, Sesame Software provides a reliable and secure backup solution that can help protect your business during a NetSuite outage. How to prepare for, and respond to, similar situations: Develop Backups and Workarounds – Companies should create backups and have alternate solutions in place for when the NetSuite system is unavailable. For instance, an additional vendor such as Sesame Software to provide a copy of their data.  Create Emergency Contacts – Companies should have pre-defined contact lists of key personnel responsible for responding to such outages, who are available and notified during times of crisis. Communication Channels – Companies should have pre-defined and tested communication channels that can be used to notify stakeholders of outages and updates. By having the right processes and preparations in place, companies can minimize the impact of a NetSuite outage and maintain business continuity. In short, the NetSuite outage serves as a reminder of the importance of backup plans and redundancy measures. Businesses should take steps to protect themselves by implementing business continuity planning, as well as exploring alternative software solutions that can be used as a backup in the event of an outage. By doing so, businesses can minimize the impact of unexpected events and ensure that they can continue to operate regardless of the challenges they may face.