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Data & Analytics – do we democratize.  60% to 80% of the strategic demand is in the Data & Analytics space depending on the business function. There is such a wealth of data available to business today to help inform them in their decision-making process but the time to enable can be lengthy and continuously develop and scale can be a challenge. I find where the challenge has been is not on ingesting the data or which platforms to host and model the data, it's more on the pace and flexibility of creating reports or insights or dashboards for the business to consume. So is the solve self service? Tradionally IT would own and develop the product end to end, but could it be time to hand over the consumable front end of the platform to business. Do we transfer that skillset to business to self create their own reports depending on their current requirements and at their own pace. Do we as IT focus on standing up a data model for business to easily interpret and access, create their own self-service reports. Excel has always been the go-to for many functions over the years. Store the data on my laptop and create the report I want on excel. What if now the laptop becomes the data cloud, and what if excel becomes PowerBI or other insights platform for the business function to leverage and develop their own reporting insights – transferring that front end consumable capability over to business… I have seen this democratization and self-service enablement have tremendous uptake and adoption by business. I wonder if its that time……. Consumable Data democratization

According to a recent survey of 600 Chief Data Officers, improving data-driven culture and governance over data are among the top priorities for data strategy in 2024. Informatica's Intelligent Data Management Cloud (#IDMC) is a Software as a Service (#SaaS) platform that addresses these priorities. With over $1B in innovation the last 5 years and continuing to re-invest in R&D at $250M/year, leveraging AI and automation to provide the best Data Management Cloud Platform on the market. If you're passionate about Data Management, don't miss out on seeing what Informatica can do for you! Results of the CDO Survey are located here: https://lnkd.in/gWNZ3e7n #DataStrategy #DataManagement #AI #Automation #DQ #DG

#Data_as_a_Service(DaaS): Unlocking the Power of Data on Demand In today's digital landscape, data is the new fuel for innovation and growth. But what if you could access, analyze, and leverage that data without heavy infrastructure or internal teams? That’s where Data-as-a-Service (DaaS) comes in. #DaaS_allows_businesses_to: -Access real-time data from anywhere, without needing massive storage systems. -Scale effortlessly, paying only for the data they use. -Focus on insights rather than data management, enabling faster decision-making. #Example: A marketing team can subscribe to customer behavior data and instantly tailor campaigns without building in-house analytics tools, speeding up their time to market. Ready to simplify your data strategy and drive smarter decisions? #DataAsAService #DaaS #DataDriven #BusinessGrowth #Innovation #RealTimeData #CloudComputing #DigitalTransformation #BigData #SmartBusiness #DataAsAService #DaaS #DataDriven #CloudComputing #BusinessInnovation #BigData #DigitalTransformation #RealTimeData #ScalableSolutions #SmartBusiness

Identifying and addressing key blind spots is critical for scalable, and ultimately, successful data analytics. Digitally transforming our operations requires a shift of mindset and practices, leaving behind the standard architectures and deployments deeply engrained in our organizational culture for the past forty years.   Streamline is revolutionizing analytics by enabling analysts to focus more on generating actionable insights from vast, real-time industrial data processed through cloud computing. Our partnership with Flow Software Inc. unites cutting-edge analytics with deep operational expertise to significantly enhance client outcomes through superior data-driven decision-making and operational efficiency.   Read more on 'Addressing Three Blind Spots To Improve Data Analysis': https://lnkd.in/gEEf6Mj6   #TheStreamlineDifference #DataAnalysis #CloudComputing #IndustrialData #RealTimeData

Why Choose Finworks Data Management? The Finworks Data Platform is a powerful, cohesive solution that manages data efficiently, securely, and transparently. https://hubs.ly/Q02Y469_0 Here’s what sets us apart: ✨ Unified Data Management: Our platform combines integrated data discovery, preparation, and governance, empowering users to access and analyse data seamlessly and securely—whether in public or private cloud, or on-premise. ⚙️ Efficiency at Scale: With advanced automation, orchestration, and self-service capabilities, Finworks accelerates data and document processing, significantly reducing manual work and enabling rapid, agile deployment. 🔍 Transparent, Intelligent Analytics: Finworks’ intelligent data management adapts to your needs, providing fast, transparent analytics with smart query acceleration for well-governed insights. 🔒 Built for Security and Compliance: Trusted by government institutions, our platform meets high standards for audit and security, ensuring your data remains safe and compliant. Whether you're scaling data operations or ensuring robust analytics, Finworks offers a flexible, user-configurable, and efficient solution designed to evolve with your organisation’s data needs.

Many organizations have faced challenges in democratizing their data, leading to a new set of data problems. End users often encounter issues with data format for visualizations and the need for additional calculations to generate reports or dashboards. Additionally, discrepancies in data terminology among departments can hinder data analysis. For instance, different teams may refer to the same data record using varied terms, making it challenging for a machine learning model or analytics team to analyze data cohesively. To address these issues, a semantic layer serves as a business representation of data, providing a unified view across an organization. It does not store actual data but acts as a metadata and abstraction layer that harmonizes data from various sources. By leveraging a semantic layer, organizations can achieve a consolidated and consistent data framework, facilitating more efficient data analysis and decision-making processes. #DataDemocratization #SemanticLayer #DataAnalysis

This article features the best 10 data and analytics platforms that aid an organization’s success. Data analysis helps organizations make appropriate decisions, improve customer understanding, enhance operational productivity, and beat the competition. Every such platform has its distinct features to enable businesses to use data efficiently. For instance, Tableau’s analytics platform is one of the most popular tools for data exploration and management. Tableau is a well-known data visualization and business intelligence company for delivers fully-integrated analytics solutions and best practice assistance. For those details on data and analytics platforms, please follow this link: https://lnkd.in/gRUUZySg

Let's talk about a fundamental aspect of data analytics that often doesn't get the spotlight it deserves: keeping that Cost Per Query (CPQ) low! 📉💻 Efficient Resource Utilization: A low CPQ ensures that resources are used efficiently. Whether you're running queries in the cloud or on-premises, optimizing costs per query allows you to make the most out of your computing resources. Scalability Without Breaking the Bank: As your data volumes and analytics demands grow, a low CPQ becomes critical for scalability. It enables your analytics infrastructure to scale without causing a spike in costs that could strain your budget. Budget Optimization: Organizations are often on a tight budget. Keeping CPQ low is a strategic move to maximize the value derived from analytics investments while staying within financial constraints. Improved ROI on Data Investments: Low CPQ translates to a higher return on investment (ROI) for your data analytics initiatives. It ensures that the insights gained from queries are achieved at a reasonable cost, increasing the overall value of your data-driven decision-making processes. Enhanced Accessibility: A low CPQ democratizes data access. It allows more stakeholders within an organization to run queries and extract insights without incurring exorbitant costs, fostering a data-informed culture across teams. Data-Driven Decision-Making: The heart of analytics lies in making informed decisions. Low CPQ enables organizations to perform extensive data analysis, empowering decision-makers with timely insights without financial bottlenecks.

Modernize data analytics with #HPE Ezmeral Data Fabric! 💡 Data Fabric unifies your data globally so that you can deliver insights more easily. Learn how it works in this solution brief, and reach out to SSA Technology with questions.

Is data management a lingering challenge for your organization? Exploring innovative solutions like Data as a Service (DaaS) could redefine your approach to data strategy. Recently, I came across an enlightening article that highlights the multifaceted benefits of DaaS. It serves as a powerful tool to democratize data, streamline processes, and enhance business insights across sectors. Imagine harnessing continuous access to high-quality data without the overhead of internal storage—this is the allure of embracing cloud-based solutions. The key takeaway is clear: organizations leveraging DaaS can focus their resources on core business functions rather than getting bogged down by data management. The ability to access precise, on-demand data is not just a trend; it’s a pathway to more agile decision-making and a competitive edge. How is your organization adapting to the evolving landscape of data services? Let’s exchange thoughts! 💬🔍 #DataAsAService #CloudSolutions #DataStrategy #DigitalTransformation #BusinessIntelligence https://lnkd.in/geG93K5S