#Data Governance Tools

[innovativeroutinesinternational]

How Data Governance Tools Improve Data Quality and Accuracy?

In the complex world of data management, many organizations rely on multiple standalone tools for data preparation, governance, and analysis. While each may excel in its specific function, their lack of integration creates layers of complexity that hinder performance and delay access to trustworthy data. This fragmented approach also makes it difficult to maintain the audit trails necessary for effective risk and control management.

Data governance tools designed to integrate these functions provide a comprehensive solution, enabling organizations to improve data quality and accuracy across the board. By consolidating processes, these tools not only streamline workflows but also establish stronger controls and visibility into the data lifecycle.

Integration Reduces Complexity

When data preparation, governance, and analytics operate in isolation, data moves through disconnected stages, often with manual intervention or translation between systems. This increases the risk of errors, inconsistencies, and delays, undermining confidence in the data. Integrated governance tools eliminate these handoffs by embedding governance controls directly into preparation and analytics workflows. This unified environment reduces friction, accelerates data availability, and simplifies management.

Audit Trails Enable Trust and Compliance

Meeting risk and control frameworks require clear, verifiable audit trails. Standalone tools rarely capture the full scope of data activities, leaving gaps that complicate compliance efforts. Integrated data governance solutions automatically record detailed logs of data changes, user actions, and policy enforcement, providing a comprehensive view of data usage. This transparency supports rigorous oversight and allows organizations to demonstrate compliance with regulatory standards.

Automated Quality Controls

Manual data validation is slow and inconsistent, creating opportunities for inaccurate data to enter business processes. Integrated governance platforms apply automated quality checks throughout the data pipeline. These controls ensure data is complete, accurate, and conforms to defined standards before it reaches analytical or operational systems. By catching issues early, organizations avoid costly rework and maintain high data integrity.

Improved Performance and Data Availability

Fragmented toolsets often introduce performance bottlenecks as data moves between incompatible systems. This impacts the speed with which data can be accessed and analyzed. Data governance tools that combine preparation, governance, and analytics capabilities optimize data processing flows, improving system performance and reducing latency. The result is faster access to high-quality, governed data.

Centralized Policy Management

Disparate tools often result in inconsistent governance policies applied across different data domains. Integrated solutions centralize policy definition and enforcement, ensuring uniform standards are applied organization-wide. This harmonization prevents conflicts and maintains consistent data quality and compliance practices.

Conclusion

By breaking down barriers between data preparation, governance, and analytics, integrated data governance tools or data masking services create a seamless, controlled data environment. This not only enhances data quality and accuracy but also delivers the auditability and performance necessary to meet today's regulatory and business demands. Organizations that adopt these solutions are better positioned to leverage their data as a reliable asset, driving confident decision-making and sustained growth.

[garymdm]

Comparing Data Governance Tools, Data Catalogs, Data Quality Tools, and Master Data Management Tools

Effective data management is essential for organizations to make informed decisions and achieve their goals. To ensure data quality, consistency, and governance, organizations often employ various tools and technologies: data governance tools, data catalogs, data quality tools, and master data management tools. But where should you focus? In this post, we will provide a high level view of the…

[where-the-water-flows]

If you know how to do it you can use someone’s phone number to find their full legal name and home address. It’s just a bit of Google and knowing what websites stores this kind of info. Saw your tags asking how a phone number could verify someone’s age

So, I appreciate you dropping into my askbox to pass that info on - genuinely, it's kind of you - and I can see how my tags came across, but what I actually meant wasn't 'how can you find info on someone just with their phone number??' -- I actually do exactly that kind of thing in my day job pretty regularly, and I have to conform to a lot of real strict ethic constraints that uh, bluntly, random discord moderators...do not.

What I was actually getting at is the fact that, assuming the hypothetical server is just using a phone number as age verification (and doing data broker/google search on that), how in the hell is it controlling for someone doing what people under the arbitrary age limit du jour have been doing since we started implementing this sort of check, ie, lying like rugs and supplying info for someone in their family/social circle instead who is older than [whatever age].

like. sure. maybe you get a phone number for age verification. awesome. plug that into your data broker/google/etc of choice, run your searches, and ok, it belongs to jane smith, 38 years old, accountant who lives in ballarat, she's totally fine to join the 18+ server! come on in jane, the smut is plentiful and the doves are extremely dead. Jane smith has a kid. jane smith's kid is 15. jane smith's kid isn't allowed in the server, because it's an 18+ only server.

jane smith's kid almost certainly knows their mum's mobile number.

how the hell can Hypothetical Server Mod control for 15 year old jane smith's kid putting in jane smith's mobile number instead of their own? and also, separately, how the hell is HSM dealing with the many -- many many many -- different privacy laws around the globe?

not just in terms of handling that sort of information on people (and also requesting it in the first place!), but also just. some countries you can get so much fucking info on someone! (the US. I'm talking about the US.)

some you can't. because privacy laws, because the info isn't publicly accessible, because it's not online and is only in hard copy at the local government office, because it's collated but only in a nonenglish language, because it's geolocked-- etc.

also, like. even if the hypothetical phone number brings up someone in the US, and also your hypothetical mod team has decided, y'know, fuck privacy laws, security of information and data ethics can take a long walk off a short pier, we're keeping this server 18+ or dying trying!

data brokers aren't...actually consistently what you would call...super accurate, or like, accurate at all. if you have a unique name, yeah, sure, you're probably kinda fucked! (assuming you're in, again, somewhere the data brokers focus) but like. if you're named something a little more common - say, james smith, or maria sanchez in the US- uh. well. there sure are a lot of people you could be, and some of them - most of them! - are over 18.

and ok, sure, a phone number is (usually) only associated with one person, but. you can get a lot of false positives, false negatives, and straight up 'we don't know 🤪', the latter of which is sometimes hidden by the databrokers going 'our best guess is that this person is: An Age!! somewhere between 0 and 200 years old. 😇'

again, I use this stuff for work, I can tell you exactly how inaccurate it can get as soon as you throw something like 'not based in the US/UK' or 'uses a nickname/multiple name formats' or 'isn't super online' or 'older than 65 and not turbo wealthy' at some of these - I've had more than one confidently tell me that [my wallet name] is an accountant based in darwin who makes horror films in alice springs on the side, and also, is 26, and had 2-3 kids with her husband Lauchlan.

literally none of these facts are true. like. even vaguely.

and that can of worms doesn't even get into if someone has requested to be removed from data broker databases and/or takes online privacy Very Seriously and/or is just fundamentally ungoogleable, which is...more common than you'd think. less common than you'd like, but more common than you think, even before google started enshittifying itself out of existence.

which is why when you're trying to do things like prove your identity to uhhh goverments, banks, etc, they want multiple forms of ID, one of which is usually a photo ID, none of which anyone should be sending to a random on discord, or, frankly, asking for from a random on discord, both bc my god privacy and security risk but also like. handling that information can actually have legal requirements!

anyway. extremely long ramble on the failings of databrokers over, I appreciate you reaching out to help explain and it was very kind of you anon, sorry that I have. uhhhh kind of a lot of professional feelings about data privacy and basic social engineering, by which I mean saying 'no I'm totally 18 pinkie swear' in the grand tradition of teens wanting to get into age locked areas ever, your forebears lied on LJ so you could lie on discord.

[insightfultake]

Why Did India’s Finance Ministry Restrict the Use of AI Tools in Offices? A Closer Look at the Decision

In a significant move, India’s Finance Ministry recently issued an advisory restricting the use of artificial intelligence (AI) tools, such as ChatGPT, Bard, and other generative AI platforms, in government offices. This decision has sparked widespread debate, with many questioning the rationale behind it. Why would a government, in an era of rapid technological advancement, curb the use of tools that promise efficiency and innovation? Let’s delve into the logic and reasoning behind this decision, including the geopolitical implications and the growing global AI race, particularly with China. Read more

[vague-humanoid]

At the California Institute of the Arts, it all started with a videoconference between the registrar’s office and a nonprofit.

One of the nonprofit’s representatives had enabled an AI note-taking tool from Read AI. At the end of the meeting, it emailed a summary to all attendees, said Allan Chen, the institute’s chief technology officer. They could have a copy of the notes, if they wanted — they just needed to create their own account.

Next thing Chen knew, Read AI’s bot had popped up inabout a dozen of his meetings over a one-week span. It was in one-on-one check-ins. Project meetings. “Everything.”

The spread “was very aggressive,” recalled Chen, who also serves as vice president for institute technology. And it “took us by surprise.”

The scenariounderscores a growing challenge for colleges: Tech adoption and experimentation among students, faculty, and staff — especially as it pertains to AI — are outpacing institutions’ governance of these technologies and may even violate their data-privacy and security policies.

That has been the case with note-taking tools from companies including Read AI, Otter.ai, and Fireflies.ai.They can integrate with platforms like Zoom, Google Meet, and Microsoft Teamsto provide live transcriptions, meeting summaries, audio and video recordings, and other services.

Higher-ed interest in these products isn’t surprising.For those bogged down with virtual rendezvouses, a tool that can ingest long, winding conversations and spit outkey takeaways and action items is alluring. These services can also aid people with disabilities, including those who are deaf.

But the tools can quickly propagate unchecked across a university. They can auto-join any virtual meetings on a user’s calendar — even if that person is not in attendance. And that’s a concern, administrators say, if it means third-party productsthat an institution hasn’t reviewedmay be capturing and analyzing personal information, proprietary material, or confidential communications.

“What keeps me up at night is the ability for individual users to do things that are very powerful, but they don’t realize what they’re doing,” Chen said. “You may not realize you’re opening a can of worms.“

The Chronicle documented both individual and universitywide instances of this trend. At Tidewater Community College, in Virginia, Heather Brown, an instructional designer, unwittingly gave Otter.ai’s tool access to her calendar, and it joined a Faculty Senate meeting she didn’t end up attending. “One of our [associate vice presidents] reached out to inform me,” she wrote in a message. “I was mortified!”

[acuvate-updates]

Maximizing Report Creation: A Comparison of Power BI and Tableau Migration

Introduction: The Evolution of Business Intelligence

In the fast-paced business world, data visualization plays a pivotal role in driving strategic decisions. The choice of a business intelligence (BI) tool significantly impacts how organizations analyze and present their data. With technology continuously evolving, staying ahead with cutting-edge BI solutions is crucial for maintaining a competitive edge.

If you are currently using Tableau but are considering a switch to Power BI, you may be wondering whether it’s worth the effort. In this blog, we’ll guide you through the transition process, explore the key advantages of Power BI, and highlight best practices to ensure a smooth migration.

Data Source Connection: New Beginnings vs. Existing Connections

Building from Scratch: In Power BI, starting fresh with report creation means establishing new data connections.

Migration from Tableau: During migration, you connect to the pre-existing data sources that were used in Tableau, ensuring continuity and reducing the need for data reconfiguration.

Rebuilding in Power BI: Replication vs. New Creation

Building from Scratch: Creating reports from scratch allows full customization of visualizations and structure without constraints from existing designs, giving greater creative freedom.

Migration from Tableau: Migration requires replicating Tableau’s reports and visualizations, often involving reverse-engineering the work done in Tableau to rebuild similar dashboards and reports in Power BI.

Read More about Why Move from Tableau to Power BI: Key Benefits Explained

Translating Logic: Adapting Tableau’s Logic to DAX in Power BI

Building from Scratch: When creating reports from scratch, you have the flexibility to design new calculations using Power BI’s DAX language.

Migration from Tableau: One of the most intricate parts of migration is converting Tableau’s calculated fields and logic into Power BI’s DAX language, ensuring that functionality is retained while adapting to Power BI’s unique environment.

Styling and Formatting: Matching the Look vs. Redesigning from Scratch

Building from Scratch: Rebuilding reports in Power BI from scratch allows for more flexibility, offering a fresh, modern design aligned with current brand aesthetics and business needs.

Migration from Tableau: During migration, it’s often necessary to match the style and design of Tableau reports to ensure a consistent user experience.

Migration Challenges: Balancing Consistency and Flexibility

Building from Scratch: Starting fresh presents no challenges in maintaining consistency with previous designs but allows for full creative control.

Migration from Tableau: The migration process is more challenging than building from scratch, as it requires careful attention to replicating Tableau’s functionality and design to ensure the Power BI reports mirror the original in both appearance and performance.

Post-Migration Support: Ensuring a Smooth Transition to Power BI

Once the migration from Tableau to Power BI is complete, providing comprehensive post-migration support is vital to ensuring a smooth transition. This includes offering training sessions, preparing documentation that outlines the differences between Tableau and Power BI, and establishing dedicated channels for users to ask questions or report issues. These efforts will facilitate user adoption and ensure the transition to Power BI is both successful and sustainable.

Know more about Tableau to Power BI: Save Costs & Gain AI-Driven Insights

Key Considerations for Migrating from Tableau to Power BI

Calculated Columns and Measures: Understanding the Differences

Tableau: Tableau’s calculated fields enable users to perform a wide variety of in-platform calculations and dynamic analysis, creating new metrics and applying complex formulas.

Power BI: Power BI uses measures for similar functionality but requires translating Tableau’s logic into Power BI’s DAX language, which might involve some fine-tuning to maintain consistency.

Chart Creation: A Shift from Modularity to Flexibility

Tableau: Tableau uses a modular approach where each chart resides in a separate worksheet. This makes it easier to analyze individual visualizations but requires more effort to manage multiple charts.

Power BI: Power BI allows multiple charts to be placed on a single page for efficient comparison and analysis, offering greater flexibility and ease of comparison within a unified workspace.

Both Power BI and Tableau provide powerful charting capabilities. Power BI’s design allows for dynamic and interconnected visualizations, while Tableau’s modular approach emphasizes individual analysis of specific datasets.

Why Choose Acuvate?

At Acuvate, we help businesses seamlessly transition their BI tools to stay ahead in today’s data-driven world. As a trusted Microsoft partner, we ensure efficiency, security, and governance in analytics modernization.

Try our migration calculator: Seamlessly Transition from Tableau to Power BI with Acuvate

How Acuvate Supports Your Power BI Migration

1. Efficient Migration Strategy

Migrating from Tableau to Power BI can be complex, but Acuvate streamlines the process. Unlike traditional BI firms, we leverage automation and best practices to accelerate migration with minimal disruption.

2. Faster Adoption with Self-Service Analytics

Power BI empowers business users with self-service analytics. Acuvate ensures teams can independently create reports while maintaining data security and governance.

3. Seamless Microsoft Integration

As a Microsoft Solutions Partner, we integrate Power BI with Office 365, Azure, and Dynamics 365 to enhance insights and decision-making.

4. Scalable and Cost-Effective Solutions

We offer flexible managed services for security compliance, data governance, and ongoing support tailored to your business needs.

5. Cutting-Edge BI Technologies

Acuvate stays ahead of BI trends, collaborating closely with Microsoft to bring the latest innovations to our clients.

6. Reliable Support & Maintenance

Beyond migration, we ensure your Power BI environment remains optimized with continuous support and performance tuning.

7. Accelerated Data Transformation

Acuvate enhances Power BI migration with AcuWeave, our advanced Microsoft Fabric accelerator. AcuWeave streamlines data ingestion, transformation, and modeling, ensuring faster insights and seamless integration with your existing BI ecosystem.

Get Started with Acuvate Today

Whether you need a full-scale migration or phased transition, Acuvate is here to guide you. Contact us to leverage Power BI for smarter insights and decision automation.

Conclusion: Unlock the Power of Advanced BI

As businesses strive for smarter analytics and improved decision-making, Power BI emerges as a powerful alternative to Tableau. Its deep integration with Microsoft products, cost efficiency, and user-friendly experience make it an excellent choice for organizations looking to enhance their BI strategy.

With a structured migration approach and best practices in place, transitioning from Tableau to Power BI can be a game-changer for your business. Don’t hesitate to make the switch and unlock new insights to drive your company forward!

Ready to migrate? Reach out to our experts today and take the first step towards an optimized business intelligence experience with Power BI.

[reallyhappyyouth]

How AI Enhances Data Quality: Exploring SaaS Solutions for Smart Data Management | AI Lens

In this insightful video, AI Lens delves into the transformative role of Artificial Intelligence in enhancing data quality within SaaS platforms. Discover how AI-driven solutions are revolutionizing data management by:​

Automating data cleansing and standardization processes.

Detecting and rectifying anomalies in real-time.

Ensuring data consistency across diverse systems.

Facilitating compliance with data governance standards.

[innovativeroutinesinternational]

The Importance of Data Governance Tools and Data Management Software

In today’s data-driven world, organizations are increasingly recognizing the importance of effective data governance and management. As businesses generate vast amounts of data, ensuring that this information is accurate, secure, and accessible becomes crucial. This article explores the role of data governance tools and data management software in fostering a robust data ecosystem. Visit Us: https://iri1.hashnode.dev/the-importance-of-data-governance-tools-and-data-management-software

[garymdm]

Time to Reinvent Data Governance

Introduction In a recent poll, I was asked (seriously) whether I felt that data governance needed to be rebranded. The inference: In spite of its importance, data governance, struggles to get traction due to the name. The issue, in my judgment, is more a question of implementation rather than branding. Data governance, often regarded as the framework that ensures data is reliable, accessible,…

[thoughtlessarse]

Apple has taken the unprecedented step of removing its strongest data security tool from customers in the UK, after the government demanded “backdoor” access to user data. UK users will no longer have access to the advanced data protection (ADP) tool, which uses end-to-end encryption to allow only account holders to view items such as photos or documents they have stored online in the iCloud storage service. Apple said it was “gravely disappointed” that it would no longer be able to offer the security feature to British customers, after the UK government asked for the right to see the data. It said the removal of the tool would make users more vulnerable to data breaches from bad actors, and other threats to customer privacy. It would also mean all data was accessible by Apple, which could share it with law enforcement if they had a warrant. Earlier this month the Home Office served Apple a request under the Investigatory Powers Act, which compels firms to provide information to law enforcement agencies, asking for the right to see users’ encrypted data, which currently not even Apple can access. After the change at 3pm on Friday, new users had no access to the ADP tool and existing users would need to disable the security feature at a later date. Messaging services like iMessage and FaceTime would remain end-to-end encrypted by default. Apple said: “We are gravely disappointed that the protections provided by ADP will not be available to our customers in the UK given the continuing rise of data breaches and other threats to customer privacy. Enhancing the security of cloud storage with end-to-end encryption is more urgent than ever before.

continue reading

Not to worry, UK iPhone users, the UK government will never misuse this power, and I'm sure the threat of security breaches is a small price to pay so that the government can snoop on you.

Time to buy a large capacity external drive if you live in the UK.

[saperp]

Master data about customers, suppliers, products, profit & cost centres, assets, etc is critical to efficient and effective business processes. If you bring your data problems with you when you move to SAP S/4 HANA implementation you will most likely be disappointed with the quality of your operational and analytical processes once you get there. SAP Master Data Governance is a multi-domain master data management solution that can help you prepare your master data for an SAP S/4HANA implementation.

[rajaniesh]

From Data to Decisions: Empowering Teams with Databricks AI/BI

🚀 Unlock the Power of Data with Databricks AI/BI! 🚀 Imagine a world where your entire team can access data insights in real-time, without needing to be data experts. Databricks AI/BI is making this possible with powerful features like conversational AI

In today’s business world, data is abundant—coming from sources like customer interactions, sales metrics, and supply chain information. Yet many organizations still struggle to transform this data into actionable insights. Teams often face siloed systems, complex analytics processes, and delays that hinder timely, data-driven decisions. Databricks AI/BI was designed with these challenges in…

[nous-infosystems]

Effective Data Governance in Power BI: Ensuring Compliance and Quality

In a world where data drives decision-making, managing data assets efficiently becomes crucial for businesses. Power BI, a leading Business Intelligence (BI) platform, provides robust capabilities for reporting and dashboards but requires a solid data governance framework to harness its full potential. Effective data governance in Power BI ensures data quality, compliance, and security, empowering business users to make informed decisions based on reliable data. This blog delves into key strategies for establishing data governance in Power BI, focusing on the adoption road-map, data model management, and compliance with regulatory requirements.

Understanding Data Governance in Power BI

Data governance in Power BI involves implementing policies and procedures to manage data quality, security, and compliance within the platform. It encompasses several aspects, including data model design, data source management, and access controls. A comprehensive data governance framework helps organizations maintain data integrity and ensure business users have reliable and secure access to BI content.

Developing a Robust Data Governance Framework

A well-defined data governance framework is essential for managing data assets effectively. This framework outlines the policies and procedures for data management, including data quality standards, access controls, and compliance requirements. In Power BI, the framework should address the following areas:

Data Model Design: The data model in Power BI serves as the foundation for reports and dashboards. A well-designed data model ensures accurate data representation and facilitates effective data analysis. The data governance framework should establish guidelines for designing data models that meet organizational needs and adhere to data quality standards.

Data Source Management: Managing data sources involves ensuring that the data ingested into Power BI is accurate, complete, and timely. The data governance framework should include procedures for validating data sources, managing data integration, and maintaining data quality throughout the data lifecycle.

Access Controls: Effective data governance requires implementing access controls to restrict data access based on user roles and responsibilities. In Power BI, this involves setting up user roles, permissions, and sensitivity labels to protect sensitive data and ensure compliance with regulatory requirements.

Strategies to Implement Data Governance in Power BI

To effectively govern data in Power BI, organizations should focus on several key strategies:

Adoption Road-map: Developing an adoption road-map helps organizations plan and execute data governance initiatives. The road-map should outline the steps for implementing governance policies, including training for business users, establishing data stewardship roles, and integrating governance practices into daily operations.

Governance Planning: Governance planning involves defining the objectives and scope of data governance initiatives. This includes identifying key stakeholders, setting governance goals, and establishing metrics to measure the effectiveness of governance practices. In Power BI, governance planning should align with the organization's overall data management strategy and address specific BI content and data assets needs.

Maintaining Data Quality: Ensuring data quality is critical to data governance. Power BI provides tools for monitoring and improving data quality, such as data validation rules, data profiling, and error reporting. The data governance framework should include procedures for maintaining data quality, addressing data issues, and implementing corrective actions as needed.

Ensuring Security and Compliance

Security and compliance are paramount in data governance, especially when dealing with sensitive data. Power BI offers several features to support security and compliance, including:

Sensitivity Labels: Sensitivity labels help classify and protect sensitive data within Power BI reports and dashboards. Labels can be applied to data sources, datasets, and reports to enforce data protection policies and ensure compliance with regulatory requirements.

Access Controls and Permissions: Implementing access controls and permissions helps restrict data access to authorized users. Power BI enables organizations to set up role-based access controls, manage user permissions, and enforce data security policies.

Regulatory Requirements: Adhering to regulatory requirements is crucial for maintaining data compliance. The data governance framework should address compliance with GDPR, HIPAA, and CCPA regulations. This includes ensuring that data handling practices align with regulatory standards and implementing measures to safeguard sensitive data.

Managing Data Assets and BI Content

Effective management of data assets and BI content is essential for successful data governance in Power BI. This involves:

Data Asset Management: Managing data assets involves tracking and controlling data throughout its lifecycle. Power BI includes monitoring data usage, managing data sources, and ensuring data quality across reports and dashboards.

BI Content Management: Managing BI content involves organizing and maintaining reports, dashboards, and other BI artifacts. This includes establishing naming conventions, version control, and documentation practices to ensure that BI content remains accurate and up to date.

Conclusion

Implementing effective data governance in Power BI is crucial for ensuring data quality, security, and compliance. By developing a robust data governance framework, focusing on key strategies such as governance planning and, maintaining data quality, and ensuring security and compliance, organizations can leverage Power BI's full potential to drive informed decision-making. A well-executed data governance strategy enhances the reliability of BI content and builds trust among business users by providing them with accurate, secure, and compliant data.

As organizations continue to rely on data for strategic decisions, prioritizing data governance in Power BI will help maintain data integrity and effectively support business objectives. By adhering to best practices and continuously refining governance practices, businesses can ensure that their Power BI implementations deliver valuable insights while meeting regulatory and security requirements.

[manageditserviceslosangeles]

Unlock the Power of Azure AI: Dive into Our Latest Blog on Essential Computing Power!

Curious about what drives today’s AI breakthroughs? From autonomous vehicles to smart assistants, it's all about robust computing power. ECF Data’s latest blog, "IT Insights: Essential Computing Power for Azure AI," reveals how Azure AI and Azure Compute Services are at the forefront of these advancements.

Discover how Microsoft’s cutting-edge tools empower researchers and businesses to push the boundaries of AI. Whether you're a tech enthusiast or a business leader, this is your guide to understanding the backbone of modern AI technology.

Ready to explore? Click here to read the full blog and see how Azure is shaping the future of AI!

LET'S CONNECT

[saad1505]

Master Data Governance Solutions | Mining Industry 

Discover how master data management solutions (MDM) enhances data accuracy, streamlines processes, and ensures compliance in the mining industry. https://www.piloggroup.com/Master-data-governance-in-mining-industries.php