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As data volumes continue to rapidly grow and organizations become increasingly data driven in the AI age, the data landscape of 2025 is poised to be more dynamic and complex than ever before.
For businesses to excel in this fast-evolving environment, chief data officers (CDOs) of the future must move beyond their traditional roles to become strategic transformation leaders. Key priorities will shape their agenda and be a driving force for success in an era of sweeping change.
The eBook “Seven Chief Data Officer (CDO) Priorities for 2025,” explores seven key priorities that will define successful data leadership in 2025. From crafting unified data strategies that feel less like governance manifestos and more like business transformation blueprints, to preparing trusted data for the AI revolution, you will learn:
The role of the CDO has undergone a significant change over the last few years—and it’s continuing to be redefined as CDOs prove their value. CDOs are now unlocking competitive advantages by implementing and optimizing comprehensive data initiatives. That’s part of the reason why organizations with a dedicated CDO are better equipped to handle the complexities of modern data ecosystems and maintain a competitive edge than those without this role.
As noted in our eBook “Seven Chief Data Officer (CDO) Priorities for 2025,” this critical position will become even more strategic. The role will highlight a distinct difference between good companies that use data and great companies that rely on data to drive every business decision, accelerate growth, and confidently embrace whatever is next.
The idea for this eBook began with a simple observation: The role of CDO has become a sort of organizational Rorschach test. Ask 10 executives what a CDO should do, and you’ll get 11 different answers, three strategic frameworks, and at least one person insisting it’s all about AI (it’s not).
While researching this piece, a fascinating pattern emerged. Data strategy isn’t just about governance and quality metrics, but about fundamental business transformation. But perhaps most intriguing is the transformation of the CDO role itself. What started as a data custodian and governance guru has morphed into something far more nuanced: Part strategist, part innovator, part ethicist, and increasingly, part business transformer.
The eBook dives deeper into these themes, offering insights and frameworks for navigating this evolution. But more than that, it attempts to capture this moment of transformation–where data leadership is becoming something new and, potentially, revolutionary.
The seven priorities outlined in the eBook aren’t just predictions; they’re emerging patterns. When McKinsey tells us that 72% of organizations struggle with managing data for AI use cases, they’re really telling us something profound about the gap between our technological ambitions and our organizational readiness. We’re all trying to build the plane while flying it–and some of us are still debating whether we need wings.
This eBook is for leaders who find themselves at this fascinating intersection of technology, strategy, and organizational change. Whether you’re a CDO looking to validate your roadmap, or an executive trying to understand why your data initiatives feel like pushing boulders uphill, we hope you’ll find something here that makes you think differently about the journey ahead.
Download the eBook if you’re curious about what data leadership looks like when we stop treating it like a technical function and start seeing it as a strategic imperative.
The post The 7 Fundamentals That Are Crucial for CDO Success in 2025 appeared first on Actian.
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I am very excited about the HCL Informix® 15 external smartblob feature.
If you are not familiar with them, external smartblobs allow the user to store actual Binary Large Object (blob) and Character Large Object (clob) data external to the database. Metadata about that external storage is maintained by the database.
Notes: This article does NOT discuss details of the smartblobs feature itself, but rather proposes a solution to make the functionality more user-friendly. For details on feature behavior, setup, and new functions, see the documentation.
At the writing of this blog, v15.0 does not have the ifx_lo_path function defined, as required below. This has been reported to engineering. The workaround is to create it yourself with the following command:
create dba function ifx_lo_path(blob) returns lvarchar external name '(sq_lo_path)' language C;
This article also does not discuss details of client programming required to INSERT blobs and clobs into the database.
The external smartblob feature was built for two main reasons:
1. Backup size
Storing blobs in the database itself can cause the database to become extremely large. As such, performing backups on the database takes an inordinate amount of time, and 0 level backups can be impossible. Offloading the actual blob contents to an external file system can lessen the HCL Informix backup burden by putting the blob data somewhere else. The database still governs the storage of, and access to, the blob, but the physical blob is housed elsewhere/externally.
2. Easy access to blobs
Users would like easy access to blob data, with familiar tools, without having to go through the database.
Using External Smartblobs in HCL Informix 15
HCL Informix 15 introduces external smartblobs. When you define an external smartblob space, you specify the external directory location (outside the database) where you would like the actual blob data to be stored. Then you assign blob column(s) to that external smartblob space when you CREATE TABLE. When a row is INSERTed, HCL Informix stores the blob data in the defined directory using an internal identifier for the filename.
Here’s an example of a customer forms table: custforms (denormalized and hardcoded for simplicity). My external sbspace directory is /home/informix/blog/resources/esbsp_dir1.
CREATE TABLE custforms(formid SERIAL, company CHAR(20), year INT, lname CHAR(20), formname CHAR(50), form CLOB) PUT form IN (esbsp);
Here, I INSERT a 2023 TaxForm123 document from a Java program for a woman named Sanchez, who works for Actian:
try(PreparedStatement p = c.prepareStatement("INSERT INTO custforms (company, year, lname, formname, form) values(?,?,?,?,?)"); FileInputStream is = new FileInputStream("file.xml")) { p.setString(1, "Actian"); p.setString(2, "2023"); p.setString(3, "Sanchez"); p.setString(4, "TaxForm123"); p.setBinaryStream(5, is); p.executeUpdate(); }
After I INSERT this row, my external directory and file would look like this:
[informix@schma01-rhvm03 resources]$ pwd /home/informix/blog/resources [informix@schma01-rhvm03 resources]$ ls -l esbsp* -rw-rw---- 1 informix informix 10240000 Oct 17 13:22 esbsp_chunk1 esbsp_dir1: total 0 drwxrwx--- 2 informix informix 41 Oct 17 13:19 IFMXSB0 [informix@schma01-rhvm03 resources]$ ls esbsp_dir1/IFMXSB0 LO[2,2,1(0x102),1729188125]
Where LO[2,2,1(0x102),1729188125]is an actual file that contains the data that I could access directly. The problem is that if I want to directly access this file for Ms. Sanchez, I would first have to figure out that this file belongs to her and is the tax document I want. It’s very cryptic!
A User-Friendly Smartblob Solution
When talking to Informix customers, they love the new external smartblobs feature but wish it could be a little more user-friendly.
As in the above example, instead of putting Sanchez’s 2023 TaxForm123 into a general directory called IFMXSB0 in a file called LO[2,2,1(0x102),1729188125, which together are meaningless to an end-user, wouldn’t it be nice if the file was located in an intuitive place like /home/forms/Actian/2024/TaxForm123/Sanchez.xml or something similar…something meaningful…how YOU want it organized?
Having HCL Informix automatically do this is a little easier said than done, primarily because the database would not intuitively know how any one customer would want to organize their blobs. What exact directory substructure? From what column or columns do I form the file names? What order? All use cases would be different.
Leveraging a User-Friendly Shadow Directory
The following solution shows how you can create your own user-friendly logical locations for your external smartblobs by automatically maintaining a lightweight shadow directory structure to correspond to actual storage locations. The solution uses a very simple system of triggers and stored procedures to do this.
Note: Examples here are shown on Linux, but other UNIX flavors should work also.
How to Set Up in 4 Steps
For each smartblob column in question
STEP 1: Decide how you want to organize access to your files.
Decide what you want the base of your shadow directory to be and create it. In my case for this blog, it is: /home/informix/blog/resources/user-friendly. You could probably implement this solution without a set base directory (as seen in the examples), but that may not be a good idea because users would unknowingly start creating directories everywhere.
STEP 2: Create a create_link stored procedure and corresponding trigger for INSERTs.
This procedure makes sure that the desired data-driven subdirectory structure exists from the base (mkdir -p), then forms a user-friendly logical link to the Informix smartblob file. You must pass all the columns to this procedure from which you want to form the directory structure and filename from the trigger.
CREATE PROCEDURE
CREATE PROCEDURE create_link (p_formid INT, p_company CHAR(20), p_year INT, p_lname CHAR(20), p_formname CHAR(50))
DEFINE v_oscommand CHAR(500); DEFINE v_custlinkname CHAR(500); DEFINE v_ifmxname CHAR(500); DEFINE v_basedir CHAR(100);
-- set the base directory LET v_basedir = '/home/informix/blog/resources/user-friendly';
-- make sure directory tree exists LET v_oscommand = 'mkdir -p ' || TRIM(v_basedir) || '/' || TRIM(p_company) || '/' || TO_CHAR(p_year); SYSTEM v_oscommand; -- form full link name LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_company) || '/' || TO_CHAR(p_year) || '/' || TRIM(p_lname) || '.' || TRIM(p_formname) || '.' || TO_CHAR(p_formid); -- get the actual location SELECT IFX_LO_PATH(form::LVARCHAR) INTO v_ifmxname FROM custforms WHERE formid = p_formid; -- create the os link LET v_oscommand = 'ln -s -f ' || '''' || TRIM(v_ifmxname) || '''' || ' ' || v_custlinkname; SYSTEM v_oscommand; END PROCEDURE
CREATE TRIGGER
CREATE TRIGGER ins_tr INSERT ON custforms REFERENCING new AS post FOR EACH ROW(EXECUTE PROCEDURE create_link (post.formid, post.company, post.year, post.lname, post.formname));
STEP 3: Create a delete_link stored procedure and corresponding trigger for DELETEs.
This procedure will delete the shadow directory link if the row is deleted.
CREATE PROCEDURE
CREATE PROCEDURE delete_link (p_formid INT, p_company CHAR(20), p_year INT, p_lname CHAR(20), p_formname CHAR(50))
DEFINE v_oscommand CHAR(500); DEFINE v_custlinkname CHAR(500); DEFINE v_basedir CHAR(100);
-- set the base directory LET v_basedir = '/home/informix/blog/resources/user-friendly';
-- form full link name LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_company) || '/' || TO_CHAR(p_year) || '/' || TRIM(p_lname) || '.' || TRIM(p_formname) || '.' || TO_CHAR(p_formid);
-- remove the link LET v_oscommand = 'rm -f -d ' || v_custlinkname; SYSTEM v_oscommand; END PROCEDURE
CREATE TRIGGER
CREATE TRIGGER del_tr DELETE ON custforms REFERENCING old AS pre FOR EACH ROW (EXECUTE PROCEDURE delete_link (pre.formid, pre.company, pre.year, pre.lname, pre.formname));
STEP 4: Create a change_link stored procedure and corresponding trigger for UPDATEs, if desired. In my example, Ms. Sanchez might get married to Mr. Simon and an UPDATE to her last name in the database occurs. I may then want to change all my user-friendly names from Sanchez to Simon. This procedure deletes the old link and creates a new one.
Notice the update trigger only must fire on the columns that form your directory structure and filenames.
CREATE PROCEDURE
CREATE PROCEDURE change_link (p_formid INT, p_pre_company CHAR(20), p_pre_year INT, p_pre_lname CHAR(20), p_pre_formname CHAR(50), p_post_company CHAR(20), p_post_year INT, p_post_lname CHAR(20), p_post_formname CHAR(50)) DEFINE v_oscommand CHAR(500); DEFINE v_custlinkname CHAR(500); DEFINE v_ifmxname CHAR(500); DEFINE v_basedir CHAR(100); -- set the base directory LET v_basedir = '/home/informix/blog/resources/user-friendly'; -- get rid of old -- form old full link name LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_pre_company) || '/' || TO_CHAR(p_pre_year) || '/' || TRIM(p_pre_lname) || '.' || TRIM(p_pre_formname) || '.' || TO_CHAR(p_formid) ; -- remove the link and empty directories LET v_oscommand = 'rm -f -d ' || v_custlinkname; SYSTEM v_oscommand; -- form the new -- make sure directory tree exists LET v_oscommand = 'mkdir -p ' || TRIM(v_basedir) || '/' || TRIM(p_post_company) || '/' || TO_CHAR(p_post_year); SYSTEM v_oscommand; -- form full link name LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_post_company) || '/' || TO_CHAR(p_post_year) || '/' || TRIM(p_post_lname) || '.' || TRIM(p_post_formname) || '.' || TO_CHAR(p_formid) ; -- get the actual location -- this is the same as before as id has not changed SELECT IFX_LO_PATH(form::LVARCHAR) INTO v_ifmxname FROM custforms WHERE formid = p_formid; -- create the os link LET v_oscommand = 'ln -s -f ' || '''' || TRIM(v_ifmxname) || '''' || ' ' || v_custlinkname; SYSTEM v_oscommand; END PROCEDURE
CREATE TRIGGER
CREATE TRIGGER upd_tr UPDATE OF formid, company, year, lname, formname ON custforms REFERENCING OLD AS pre NEW as post FOR EACH ROW(EXECUTE PROCEDURE change_link (pre.formid, pre.company, pre.year, pre.lname, pre.formname, post.company, post.year, post.lname, post.formname));
Results Example
Back to our example.
With this infrastructure in place, now in addition to the Informix-named file being in place, I would have these user-friendly links on my file system that I can easily locate and identify.
INSERT
[informix@schma01-rhvm03 2023]$ pwd
/home/informix/blog/resources/user-friendly/Actian/2023 [informix@schma01-rhvm03 2023]
$ ls Sanchez.TaxForm123.2
If I do an ls -l, you will see that it is a link to the Informix blob file.
[informix@schma01-rhvm03 2023]$ ls -l total 0 lrwxrwxrwx 1 informix informix 76 Oct 17 14:20 Sanchez.TaxForm123.2 -> /home/informix/blog/resources/esbsp_dir1/IFMXSB0/LO[2,2,1(0x102),1729188126]
UPDATE
If I then update her last name with UPDATE custforms SET lname = ‘Simon’ where formid=2,my file system now looks like this:
[informix@schma01-rhvm03 2023]$ ls -l lrwxrwxrwx 1 informix informix 76 Oct 17 14:25 Simon.TaxForm123.2 -> /home/informix/blog/resources/esbsp_dir1/IFMXSB0/LO[2,2,1(0x102),1729188126]
DELETE
If I then go and DELETE this form with DELETE FROM custforms where formid=2, my directory structure looks like this:
[informix@schma01-rhvm03 2023]$ pwd /home/informix/blog/resources/user-friendly/Actian/2023 [informix@schma01-rhvm03 2023]$ ls [informix@schma01-rhvm03 2023]$
We Welcome Your Feedback
Please enjoy the new HCL Informix15 external smartblob feature.
I hope this idea can make external smartblobs easier for you to use. If you have any feedback on the idea, especially on enhancements or experience in production, please feel free to contact me at mary.schulte@hcl-software.com. I look forward to hearing from you!
Find out more about the launch of HCL Informix 15.
Notes
1. Shadow directory permissions. In creating this example, I did not explore directory and file permissions, but rather just used general permissions settings on my sandbox server. Likely, you will want to control permissions to avoid some of the anomalies I discuss below.
2. Manual blob file delete. With external smartblobs, if permissions are not controlled, it is possible that a user might somehow delete the physical smartblob file itself from its directory. HCL Informix, itself, cannot control this from happening. In the event it does happen, HCL Informix does NOT delete the corresponding row; the blob file will just be missing. There may be aspects to links that can automatically handle this, but I have not investigated them for this blog.
3. Link deletion in the shadow directory. If permissions are not controlled, it is possible that a user might delete a logical link formed by this infrastructure. This solution does not detect this. If this is an issue, I would suggest a periodic maintenance job that cross references the shadow directory links to blob files to detect missing links. For those blobs with missing links, write a database program to look up the row’s location with the IFX_LO_PATH function, and reform the missing link.
4. Unique identifiers. I highly recommend using unique identifiers in this solution. In this simple example, I used formid. You don’t want to clutter things up, of course, but depending on how you structure your shadow directories and filenames, you may need to include more unique identifiers to avoid directory and link names duplication.
5. Empty directories. I did not investigate if there are options to rm in the delete stored procedure to clean up empty directories that might remain if a last item is deleted.
6. Production overhead. It is known that excessive triggers and stored procedures can add overhead to a production environment. For this blog, it is assumed that OLTP activity on blobs is not excessive, therefore production overhead should not be an issue. This being said, this solution has NOT been tested at scale.
7. NULL values. Make sure to consider the presence and impact of NULL values in columns used in this solution. For simplicity, I did not handle them here.
Informix is a trademark of IBM Corporation in at least one jurisdiction and is used under license.
The post User-Friendly External Smartblobs Using a Shadow Directory appeared first on Actian.
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Predictions are funny things. They often seem like a bold gamble, almost like trying to peer into the future with the confidence we inherently lack as humans. Technology’s rapid advancement surprises even the most seasoned experts, especially when it progresses exponentially, as it often does. As physicist Albert A. Bartlett famously said, “The greatest shortcoming […]
The post AI Predictions for 2025: Embracing the Future of Human and Machine Collaboration appeared first on DATAVERSITY.
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Unlocking the value of data is a key focus for business leaders, especially the CIO. While in its simplest form, data can lead to better insights and decision-making, companies are pursuing an entirely different and more advanced agenda: the holy grail of data monetization. This concept involves aggregating a variety of both structured and unstructured […]
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The manufacturing industry is in the midst of a digital revolution. You’ve probably heard these buzzwords: Industry 4.0, IoT, AI, and machine learning– all terms that promise to revolutionize everything from assembly lines to customer service. Embracing this digital transformation is key in improving your competitive advantage, but new technology doesn’t come without its own challenges. Each new piece of technology needs one thing to deliver innovation: data.
Data is the fuel powering your tech engines. Without the ability to understand where your data is, whether it’s trustworthy, or who owns the datasets, even the most powerful tools can overcomplicate and confuse the best data teams. That’s where modern data discovery solutions come in. They’re like the backstage crew making sure everything runs smoothly– connecting systems, tidying up the data mess, and making sure everyone has exactly what they need, when they need it. That means faster insights, streamlined operations, and a lower total cost of ownership (TCO). In other words, data access is the key to staying ahead in today’s fast-paced, highly competitive, increasingly sensitive manufacturing market.
Data from all aspects of your business is siloed– whether it’s coming from sensors, legacy systems, cloud applications, suppliers or customers– trying to piece it all together is daunting, time-consuming, and just plain hard. Traditional methods are slow, cumbersome, and definitely not built for today’s needs. This fragmented approach not only slows down decision-making, but keeps you from tapping into valuable insights that could drive innovation. And in a market where speed is everything, that’s a recipe for falling behind.
So the big question is: how can you unlock the true potential of your data?
So how do you make data intelligence into a streamlined, efficient process? The answer lies in modern data discovery solutions– the unsung catalyst of a digital transformation motion. Rather than simply integrating data sources, data discovery solutions excel in metadata management, offering complete visibility into your company’s data ecosystem. They enable users– regardless of skill level– to locate where data resides and assess the quality and relevance of the information. By providing this detailed understanding of data context and lineage, organizations can confidently leverage accurate, trustworthy datasets, paving the way for informed decision-making and innovation,
One of the biggest hurdles in data integration is connecting to a variety of data sources, including legacy systems, cloud applications, and IoT devices. Modern data discovery tools like Zeenea offer easy connectivity, allowing you to extract metadata from various sources seamlessly. This unified view eliminates silos and enables faster, more informed decision-making across the organization.
Metadata is the backbone of effective data discovery. Advanced metadata management capabilities ensure that data is well-organized, tagged, and easily searchable. This provides a clear context for data assets, helping you understand the origin, quality, and relevance of your data. This means better data search and discoverability.
A data discovery knowledge graph serves as an intelligent map of your metadata, illustrating the intricate relationship and connections between data assets. It provides users with a comprehensive view of how data points are linked across systems, offering a clear picture of data lineage– from origin to current state. The visibility into the data journey is invaluable in manufacturing, where understanding the flow of information between production data, supply chain metrics, and customer feedback is critical. By tracing the lineage of data, you can quickly assess its accuracy, relevance, and context, leading to more precise insights and informed decision-making.
A data marketplace provides a centralized hub where you can easily search, discover, and access high-quality data. This self-service model empowers your teams to find the information they need without relying on IT, accelerating time to insight. The result? Faster product development cycles, improved process efficiency, and enhanced decision-making capabilities.
Modern data discovery platforms prioritize user experience with intuitive, user-friendly interfaces. Features like natural language search allow users to query data using everyday language, making it easier for non-technical users to find what they need. This democratizes access to data across the organization, fostering a culture of data-driven decision-making.
Traditional metadata management solutions often come with a hefty price tag due to high infrastructure costs and ongoing maintenance. In contrast, modern data discovery tools are designed to minimize TCO with automated features, cloud-based deployment, and reduced need for manual intervention. This means more efficient operations and a greater return on investment.
By leveraging a comprehensive data discovery solution, manufacturers can achieve several key benefits:
With quick access to quality data, teams can identify trends and insights that drive product development and process optimization.
Automated implementation and seamless data connectivity reduce the time required to gather and analyze data, enabling faster decision-making.
Advanced metadata management and knowledge graphs help streamline data governance, ensuring that users have access to reliable, high-quality data.
A user-friendly data marketplace democratizes data access, empowering teams to make data-driven decisions and stay ahead of industry trends.
With low TCO and reduced dependency on manual processes, manufacturers can maximize their resources and allocate budgets towards strategic initiatives.
Data is more than just a resource—it’s a catalyst for innovation. By embracing advanced metadata management and data discovery solutions, you can find, trust, and access data. This not only accelerates time to market but also drives operational efficiency and boosts competitiveness. With powerful features like API-led automation, a data discovery knowledge graph, and an intuitive data marketplace, you’ll be well-equipped to navigate the challenges of Industry 4.0 and beyond.
Ready to accelerate your innovation journey? Explore how Actian Zeenea can transform your manufacturing processes and give you a competitive edge.
Learn more about how our advanced data discovery solutions can help you unlock the full potential of your data. Sign up for a live product demo and Q&A.
The post Accelerating Innovation: Data Discovery in Manufacturing appeared first on Actian.
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You never know what’s going to happen when you click on a LinkedIn job posting button. I’m always on the lookout for interesting and impactful projects, and one in particular caught my attention: “Far North Enterprises, a global fabrication and distribution establishment, is looking to modernize a very old data environment.” I clicked the button […]
The post Mind the Gap: Architecting Santa’s List – The Naughty-Nice Database appeared first on DATAVERSITY.
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There is an urgent reality that many manufacturing leaders are facing, and that’s data silos. Valuable information remains locked within departmental systems, hindering your ability to make strategic, well-informed decisions. A data catalog and enterprise data marketplace solution provides a comprehensive, integrated view of your organization’s data, breaking down silos and enabling true collaboration.
In your organization, each department maintains its own critical datasets– finance compiles detailed financial reports, sales leverages CRM data, marketing analyzes campaign performance, and operations tracks supply chain metrics. But here’s the challenge: how confident are you that you even know what data is available, who owns it, or if it’s quality?
The issue goes beyond traditional data silos. It’s not just that the data is isolated– it’s that your teams are unaware of what data even exists. This lack of visibility creates a blind spot. Without a clear understanding of your company’s data landscape, you face inefficiencies, inconsistent analysis, and missed opportunities. Departments and up duplicating work, using outdated or unreliable data, and making decisions based on incomplete information.
The absence of a unified approach to data discovery and cataloging means that even if the data is technically accessible, it remains hidden in plain sight, trapped in disparate systems without any context or clarity. Without a comprehensive search engine for your data, your organization will struggle to:
Now, imagine the transformative potential if your team could search for and discover all available data across your organization as easily as using a search engine. Implementing a robust metadata management strategy—including data lineage, discovery, and cataloging—bridges the gaps between disparate datasets, enabling you to understand what data exists, its quality, and how it can be used. Instead of chasing down reports or sifting through isolated systems, your teams gain an integrated view of your company’s data assets.
This approach can transform the way each department operates, fostering a culture of informed decision-making and reducing inefficiencies:
This strategy isn’t about collecting more data—it’s about creating a clearer, more reliable picture of your entire business. By investing in a data catalog, you turn fragmented insights into a cohesive, navigable map that guides your strategic decisions with clarity and confidence. It’s the difference between flying blind and having a comprehensive navigation system that leads you directly to success.
When you prioritize data intelligence with a catalog as a cornerstone, your organization gains access to a powerful suite of benefits:
Data silos are more than just an operational inconvenience—they are a barrier to your company’s growth and innovation. By embracing data cataloging, lineage, and governance, you empower your teams to collaborate seamlessly, leverage accurate insights, and make strategic decisions with confidence. It is time to break down the barriers, integrate your metadata, and unlock the full potential of your organization’s data.
Are you ready to eliminate data silos and gain a unified view of your operations? Discover the power of metadata management with our comprehensive platform. Visit our website today to learn more and sign up for a live product demo and Q&A.
The post From Silos to Synergy: Data Discovery for Manufacturing appeared first on Actian.
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