An exhaustive course covering Regression, Classifications, Clustering, Text Mining, Sequence analysis, Sentiment analysis, Text analysis, using tools like, R Studio, Jupyter Note book, Orange, KNIME, Big ML and RapidMiner
Offers insights of Data Governance, its needs, policies, maturity and processes needed to have an effective program to manage data. Introduction to ISACA data maturity model and methods to implement and manage the governance office
LinkedIn Learning path that offers the fundamental stages of data science work, from Statistics and Systems Engineering to Data Mining and Machine Learning, source, explore, and communicate with data through graphs and statistics.
This course shows how to use analytics to make data-driven decisions and gain competitive advantage,explore the differences between predictive and prescriptive analytics, and find out how to formulate questions,variety of simple techniques: averages, sampling, cherry picking, forecasting, and correlation and causality
Certificate of completion leading during times of changeUtkarsha B
Managers and leaders are constantly confronted with change. Learn the specific techniques to plan your change effort as well as how to address the cultural and emotional challenges that arise during organizational changes.
This is a hands-on course for big data using Cloudera cluster and Hue to work with Hive database, create datamart for sample data engineering tasks like design of back office and client databases, facts , dimension tables , joining, creating views for ease of view
Applied statistics with lots of fun and exercises related to Mean, Median, Mode, Std. Deviation, Probability, Conditional probability, Bell Curve, Discrete and Continuous variables, Z-order and Z-order tables.
Certificate of completion being an effective team memberVaibhav Kakkar
A very detailed explanation of how a team functions, what kind of problems a team or an individual faces and how can we solve them and manage the whole team.
In this course I learnt how to build out IoT applications with Google Cloud IoT Core,provision and secure edge devices, set up a virtual device, set up a connected edge device, and use an IoT gateway,
Enterprise agile - disciplined agile DA versus SpotifyVijayananda Mohire
Learn about the DA lifecycle and roles, its pragmatic approach to agile, and some of the challenges you may encounter with the framework. Then compare the Spotify model of squads, chapters, tribes, and guilds.
Managing budget constrained projects with microsoft projectVijayananda Mohire
This course explores how to best set up and manage projects facing budget constraints. Teaches how to set up project costs: everything from setting project cost options to assigning budget cost, work resources,enter cost values and review and manage project costs
An exhaustive course covering Regression, Classifications, Clustering, Text Mining, Sequence analysis, Sentiment analysis, Text analysis, using tools like, R Studio, Jupyter Note book, Orange, KNIME, Big ML and RapidMiner
Offers insights of Data Governance, its needs, policies, maturity and processes needed to have an effective program to manage data. Introduction to ISACA data maturity model and methods to implement and manage the governance office
LinkedIn Learning path that offers the fundamental stages of data science work, from Statistics and Systems Engineering to Data Mining and Machine Learning, source, explore, and communicate with data through graphs and statistics.
This course shows how to use analytics to make data-driven decisions and gain competitive advantage,explore the differences between predictive and prescriptive analytics, and find out how to formulate questions,variety of simple techniques: averages, sampling, cherry picking, forecasting, and correlation and causality
Certificate of completion leading during times of changeUtkarsha B
Managers and leaders are constantly confronted with change. Learn the specific techniques to plan your change effort as well as how to address the cultural and emotional challenges that arise during organizational changes.
This is a hands-on course for big data using Cloudera cluster and Hue to work with Hive database, create datamart for sample data engineering tasks like design of back office and client databases, facts , dimension tables , joining, creating views for ease of view
Applied statistics with lots of fun and exercises related to Mean, Median, Mode, Std. Deviation, Probability, Conditional probability, Bell Curve, Discrete and Continuous variables, Z-order and Z-order tables.
Certificate of completion being an effective team memberVaibhav Kakkar
A very detailed explanation of how a team functions, what kind of problems a team or an individual faces and how can we solve them and manage the whole team.
In this course I learnt how to build out IoT applications with Google Cloud IoT Core,provision and secure edge devices, set up a virtual device, set up a connected edge device, and use an IoT gateway,
Enterprise agile - disciplined agile DA versus SpotifyVijayananda Mohire
Learn about the DA lifecycle and roles, its pragmatic approach to agile, and some of the challenges you may encounter with the framework. Then compare the Spotify model of squads, chapters, tribes, and guilds.
Managing budget constrained projects with microsoft projectVijayananda Mohire
This course explores how to best set up and manage projects facing budget constraints. Teaches how to set up project costs: everything from setting project cost options to assigning budget cost, work resources,enter cost values and review and manage project costs
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
LinkedIn Learning Path Certificate of Completion - "Master In-Demand Professional Soft Skills"
1. Certificate of Completion
Congratulations, Dean Pangelinan
Master In-Demand Professional Soft Skills
Learning Path completed on Feb 04, 2021 at 07:57PM UTC • 9 hours 29 min
By continuing to learn, you have expanded your perspective, sharpened your
skills, and made yourself even more in demand.
Top skills covered
Critical Thinking, Emotional Intelligence, Life Skills, Resiliency,
Leadership, Communication, Personal Development
Head of Content Strategy, Learning
LinkedIn Learning
1000 W Maude Ave
Sunnyvale, CA 94085
Certificate Id: Aee9Ti7s5iwjrGwRkiSMXtDyP99b