Product Launches

Announcing Actian ODBC Connector in the Tableau Extension Gallery

Chris Clark

August 21, 2020

abstract concept of connecting data sources with confidence

There’s now an easier way to connect to Actian Data Platform from Tableau using the new Actian ODBC connector available in the Tableau Extension Gallery.

Actian and Tableau have partnered for the past several years to deliver a seamless connectivity experience to our customers. To take advantage of Tableau’s latest analytical features, the two teams engaged in the development of an improved Tableau connector leveraging Tableau’s new Connector SDK. The benefits you will see with the new connector is support for Level of Detail (LOD) Expressions, no need for a TDC file, as well as a more streamlined connection dialog as well as easier updates when new features are added.

The new connector is featured in the Tableau Extensions Gallery, where users can download the connector and quickly start their analysis in Tableau! The new connector for Actian Data Platform is created and supported by Actian and is available for Tableau Desktop and Tableau Server.

Users should get the latest connector from Tableau, but if you want to change how things work, you can pull the code down and modify it to suit your purpose. The Actian connector is open source so you can see how the sausage is made by checking out this link. There is also early access to a version of a JDBC-based connector (the ODBC one is the recommended connector with Tableau).

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About Chris Clark

Chris Clark is the Engineering Manager for Connectivity, OpenROAD, Enterprise Access, and EDBC at Actian. With frontline support and engineering roots, Chris has guided customers through seamless upgrades and integrations, ensuring incremental growth with minimal disruption. He has published technical papers on bridging legacy systems with modern architectures. Chris's blog posts dive into connectivity solutions, API integration, and modernization strategies for Actian's suite of products. Explore his articles for step-by-step implementation tips.
Data Platform

The Impact of Updates on Data Warehouse Performance

Actian Corporation

August 20, 2020

Update software application and hardware upgrade technology concept

When companies project data warehouse growth, they often look at a curve that mimics the growth of data in source systems. This approach works if all you are concerned with is storage growth. What is commonly overlooked is the compute growth curve for processing updates to your data. As IT systems become more interconnected, data updates in one place have a ripple effect as they are replicated elsewhere. Your data warehouse then receives updates from all impacted data sources, not just the place where the change was initiated. If the computed growth isn’t planned for and accommodated in your data warehouse architecture and infrastructure, performance is likely to suffer.

The Snowball Effect on Lag Times

Data warehouse performance is a critical thing to keep on top of. If you start getting backlogged in processing data updates, the problem keeps getting worse. Keep in mind; that updates are streaming data. If your data warehouse is only able to process 9 out of 10 requested units every second, that means 1 unit goes into a queue. That may not seem like a big deal, but if the situation continues for 2 minutes, you then have 120 units in the queue and a 13-second lag time. If the situation persists for an hour, there will be 3600 units in the queue and a 6.6-minute lag time for processing. Play this out over a business day, and you can see that this becomes an overwhelming problem very quickly.

Why is This Important?

Data warehouse performance may not seem like a big issue in the context of scheduled reports and batch queries. Where it becomes problematic is in the context of modern “digitally transformed” business processes that rely on data warehouses as a point of aggregation for real-time operational metrics that span multiple source systems. Take, for example, a manufacturing facility with different production lines. This facility will have lots of sensors and smart machinery collecting data and streaming it to a data warehouse where it is combined with materials supply information, product quality data (from testing), and outbound logistics data. The data warehouse enables data from all of the smart systems to be aggregated together into a set of end-to-end datasets that can power the dashboards that facility operators use to keep things running smoothly. If performance issues in the data warehouse cause updates from source systems to be delayed, problems cannot be identified/remediated in real time, and the business loses the agility that it requires to run optimally.

Actian Addresses the Data Warehouse Performance Challenge

The Actian hybrid cloud data warehouse addresses the performance challenge and minimizes the risk of update lag time in 3 key ways.

  1. Dynamic Cloud-Scale Compute. Actian leverages the flexible nature of cloud infrastructure to adjust compute resources to match processing needs on-demand. If you see an increase in data updates due to data growth or a spike, Actian can adjust infrastructure resources to provide the needed capacity. You can’t do this with an on-premises infrastructure that is constrained by fixed hardware capacity.
  2. Vector Processing. Vector processing enables large data sets to be processed more efficiently, lowering the overall compute load on the system.
  3. Maximizing Hardware Utilization. Actian is designed to leverage CPU chip cache for execution processing, and every available CPU core to minimize infrastructure waste.  Most data warehouse systems fail to use all available CPU capacity and leverage RAM memory for execution processing – both reduce the capacity for high-performance processing.

At the end of the day, your data warehouse’s ability to maintain high performance when processing updates comes down to supply and demand for compute capacity. You can’t really control the demand for updates (unless you want to unplug some source systems or slow down your business). The piece of this you can control is your data warehouse’s capacity for processing these updates. Actian provides the highest performing solution on the market with a combination of cloud-scale resources, efficient use of hardware resources, and vectorized array-at-a-time processing. With Actian, you can spend more time focusing on growing your business and less time worrying about whether your data warehouse can keep up.

To learn more, visit www.actian.com/data-platform.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.
Data Integration

What is Enterprise Data Integration, and Why Does it Matter?

Actian Corporation

August 19, 2020

data integration being written in chalk

Summary

This blog explains enterprise data integration (EDI) — the strategic process of merging data across business units, partners, or during mergers—to create unified, scalable, secure, and insightful data ecosystems that support digital transformation and executive decision-making.

  • Unify siloed data for better insights: By integrating data from disparate sources—on‑premises, cloud, mobile, IoT—an organization gains a centralized, real-time view that enhances analytics, reporting, and C-level dashboards.
  • Boost agility, security & scalability with IPaaS: Modern iPaaS platforms (like Actian DataConnect) support flexible, scalable, and secure integration across hybrid environments—avoiding the high maintenance costs of point-to-point solutions.
  • Enable AI, BI & digital transformation: A robust EDI foundation ensures data availability and quality, empowering AI systems, enterprise BI tools, and digital workflows to drive faster, data‑driven decisions.

Enterprise data integration is the merging of data across two or more organizations. This scenario is most commonly found when companies are going through mergers or acquisitions, and data from the two companies needs to be brought together. Other scenarios for enterprise data integration are joint partnerships (where two or more companies work together under the umbrella of a shared business entity) and integration across different business units within an enterprise conglomerate. In any of these scenarios, effective enterprise data integration requires a combination of organizational politics, effective data architecture, and scalable data integration techniques.

This has become a very important topic for many business and IT executives over the past few years as companies go through the digital transformation of their business processes, leverage virtualized supply chains for delivery, and executive decision-makers become more comfortable with leveraging analytics and data to inform decision-making. Siloed organizational structures are being collapsed; siloed business processes are being rationalized and modernized; fragmented IT systems are being rationalized, and siloed data needs to be integrated to provide an all-up view of the enterprise.

Why Enterprise Data Integration is Important

Organizations that fail to implement an enterprise data integration strategy effectively will find it difficult to reap sustainable value from digital transformation initiatives.  Modernized business processes rely on integrated data for efficiencies and as an anchor point for rich user experiences.  Artificial Intelligence systems that are being deployed to provide next-generation customer experiences are driven by data.  If artificial intelligence (AI) does not have access to data from across the enterprise, it will be severely limited in the value it can provide.

Executive decision-makers are increasingly looking to enterprise dashboarding solutions like Tableau and Microsoft Power BI to provide them with all-up views across their organizations.  These enterprise business intelligence platforms are intended to provide integrated dashboards that span different source systems – obscuring the complexity introduced by IT system implementations and enabling the executive to view data in business terms.  Executives don’t want to go to multiple dashboards and reporting systems; they want all their data in one place, integrated, organized, and curated into views that they can easily understand.   If they have these views, they can quickly identify issues needing their attention with supporting information so they can make responsive decisions.  Without integrated enterprise data, the executive’s ability to act is compromised, and enterprise business agility suffers.

Why You Need an IPaaS Solution to Enable Enterprise Data Integration

Yes, you can achieve enterprise data integration through point-to-point connections – but you are going to spend more time and money than you need to achieve the desired outcomes, and it is going to cost you more to operate and maintain over time. If you want to be agile, if you want your data to be secure, if you want your solution to be scalable and flexible – you need to build your enterprise data integration on an IPaaS (Integration Platform as a Service) foundation.

An IPaaS solution provides three key characteristics that are critical for achieving a successful, sustainable enterprise data integration capability.

  1. Flexibility – Ability to connect anything, anytime, anywhere. Your enterprise is diverse, and if you are connecting data across organizations, flexibility is even more important. On-prem, in the cloud, mobile devices, deployed infrastructure, IoT – IPaaS supports it all.  You need the ability to integrate anything because, eventually, you will want to integrate everything.
  2. Scalability – As your business grows and you modernize your IT systems, your data footprint will grow exponentially. Your IPaaS solution needs to be able to scale to support this growth without sacrificing performance or overburdening you with overhead costs.
  3. Secure Management – Information Security is top of mind for modern companies. An IPaaS solution provides a centralized place to manage integrations, source system credentials, and monitor the flow of data across your organization.  IPaaS can help you lower your infosec risk.

Actian DataConnect is a leading IPaaS solution that provides the technology platform you’ll need to achieve your enterprise data integration objectives.  Through a highly scalable hybrid deployment model, robust integration design capabilities, and automated deployment capabilities – DataConnect can help you deliver more effectively and faster than other solutions. To learn more, visit DataConnect.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.