Zeed

Our CEO Zainulabedin Shah, brought the energy to today’s episode of THINK Business with Jon Dwoskin! From insights on data and AI to some real talk on mentorship, this conversation is a must-listen. Catch all the action here!

At Zeed, we believe enablement and education are the true engines of transformation. When your team understands why and how to leverage analytics, magic happens—data turns into decisions, and decisions turn into success! Discover how our enablement process can unlock the power of your data. #DataTalks #ZeedListens

Data, Data Everywhere, but What Does It Mean? Data is like a pile of LEGO bricks - each piece has potential, but without sorting and assembling them, you are not building anything meaningful. At Zeed, we do more than sort your data. We structure it, visualize it, and most importantly, we build a story to create value for your business. A great story does not simply display the data - it helps you see the house beyond the bricks! 🏠 If you are looking to transform your data into a story that drives action, let us help you build something together. #DataStorytelling #Analytics #DataVisualization #BusinessIntelligence #DataTalks #ZeedListens

If your Executives are not fully aligned on organizational priorities, Zeed can build your data strategy in order to drive cross-functional alignment.

The first step is building a scalable data strategy, is understanding what data is.

Excited to announce that Zeed offers expertise in developing large language models (LLMs) to enhance our clients' data-driven insights and automation capabilities. Let's unlock new possibilities together! Data talks. Zeed listens #ZeedListens #AI #LLM

Business Value of Data without Data Strategy Business Strategy - Data Strategy ≠ Business Value Analytics - Data Strategy ≠ Business Value AI - Data Strategy ≠ Business Value Business Value of Data with Data Strategy and Zeed Business Strategy + Data Strategy + Zeed = Business Value Analytics + Data Strategy + Zeed = Business Value AI + Data Strategy + Zeed = Business Value Data talks. Zeed listens. #zeedlistens #datastrategy #datainformeddecision #businessvalue

Data is the most precious resource in today's business world. We often tend to think about the functions of data: analytics, integrations, or AI, rather than what data is as a resource. In the same way, water has many functions: quenching thirst, cleaning, or enabling transportation just to name a few. Water's greatest value, however, is as a resource which enables these functions. Just. Like. Data! Data aggregration companies masquerade as "tech companies". Google, Apple, Meta, Tesla, and many others have all developed products and services to consume our data. Why? Data is the fuel for the age of information and digitalization. Enabling use of this data is what creates value for these companies, and their shareholders. An effective data strategy is the foundation of any successful organization. If your business needs help developing a data strategy to translate your business strategy into business value, we can help. How? We speak data! Make the most of your data resources to unlock the value your data holds. Data talks. Zeed listens. #zeedlistens #datastrategy #analytics #AI #dataisaspreciousaswater

What lessons did the Mughal Dynasty teach us about data strategy? Here are a few reflections while basking in the glow of the Badshahi Mosque in Lahore, one of the world's most famous pieces of Mughal architecture. The mosque was built between 1671 and 1673 by the Mughal emperor Aurangzeb, whose father Shah Jahan built the Taj Mahal. However, the importance of data strategy began with his great-grandfather Akbar the Great. Data Collection Akbar's administration conducted detailed surveys to gather data on land, agriculture, and population, which was documented in the Ain-i-Akbari. Our Lesson: Organizations should implement systematic and thorough data collection methods to ensure we have a complete and accurate dataset for making informed decisions. Decentralized Data Management Local governors, or Subedars, managed regional data collection and administration while reporting to the central government, allowing for tailored and relevant data. Our Lesson: Decentralizing data management across departments or regions ensures that data is context-specific and relevant, while still maintaining centralized oversight for consistency. Data-Driven Decision Making Mughal rulers used collected data to make informed decisions on taxation, military campaigns, and governance reforms, which contributed to the empire's stability and efficiency. Our Lesson: Leveraging data to drive strategic decisions helps organizations respond more effectively to challenges and opportunities, leading to improved outcomes and competitive advantage. Transparency and Accountability The Mughal administration's reliance on data contributed to transparency and accountability. Local administrators were accountable for the data they reported and the decisions they made based on available data. Our Lesson: A robust data strategy should include mechanisms for transparency and accountability. Clear documentation and accountability measures help maintain data integrity and trust in the data system. Adaptability and Flexibility The Mughals were adaptable and flexible in their approach, modifying their strategies based on changing conditions and new data. This adaptability helped them manage diverse and dynamic territories effectively. Our Lesson: A data strategy should be adaptable and flexible, allowing for adjustments based on new insights and changing circumstances. This ensures the strategy remains relevant and effective over time. Data strategy is absolutely essential to driving organizations forward. If your leaders are not data literate, it is never too late to start incorporating data into organizational thinking. A business strategy without an integrated data strategy, is no strategy at all. If the Mughals were able to rule for over 300 years using the resources of their own era to execute their organizational data strategy, imagine what they could have accomplished with if they knew Excel. 😁 Data talks. Zeed listens. #zeedlistens #datastrategy #mughaldynasty

A walk down memory lane to relive the buzzwords which defined the future of data and analytics. How much progress has your organization made down the boulevard of buzzword path? 2010 Big Data: Refers to extremely large datasets that may be analyzed computationally to reveal patterns, trends, and associations. Data Mining: The process of discovering patterns and knowledge from large amounts of data. 2011 NoSQL: A type of database design that provides flexible schemas for the storage and retrieval of data. Hadoop: An open-source framework for storing data and running applications on clusters of commodity hardware. 2012 Data Scientist: A role that involves using scientific methods, processes, algorithms, and systems to extract insights from data. Predictive Analytics: Techniques that use historical data to predict future outcomes. 2013 Machine Learning: A subset of artificial intelligence involving the development of algorithms that allow computers to learn from and make predictions based on data. Real-Time Data: Data that is delivered immediately after collection without delay. 2014 Data Lake: A storage repository that holds a vast amount of raw data in its native format. Self-Service BI: Tools that enable business users to access and work with corporate data even if they do not have a background in statistical analysis or data mining. 2015 Data Governance: The management of data availability, usability, integrity, and security in enterprise systems. 2016 Deep Learning: A subset of machine learning involving neural networks with many layers. 2017 Augmented Analytics: The use of machine learning and natural language processing to automate data preparation, insight generation, and insight explanation. 2018 Blockchain: A decentralized ledger of all transactions across a network. 2019 Data Fabric: An architecture and set of data services that provide consistent capabilities across a choice of endpoints spanning hybrid multicloud environments. 2020 Cloud Data Platform: Platforms that provide comprehensive solutions for managing data storage, processing, and analytics in the cloud. 2021 DataOps: A collaborative data management practice focused on improving the communication, integration, and automation of data flows between data managers and data consumers across an organization. 2022 Federated Learning: An ML technique that trains an algorithm across multiple decentralized edge devices or servers holding local data samples. 2023 Data Mesh: A decentralized approach to data architecture, emphasizing domain-oriented ownership and self-serve data infrastructure. 2024 Generative AI: AI systems which can generate new data similar to the data they were trained on, including text, images, and other content. Management buzzwords are like cotton candy, they taste good for a moment, then they evaporate. - Stephen Covey. Translate buzzwords into action! Data talks. Zeed listens. #zeedlistens #datastrategy #generativeAI