You need to analyze data on the go. Which mobile communication tools should you use?

It is always interesting to have multiple options, in my personal experience I am using multiple providers to segregate the type of data. Part of the decision lies also on the device you use, or ecosystem you choose. As an example I use Google for work, company provided, Apple for personal usage, and backup of my iPhone and Mac, Dropbox to share large files with other, and eventually Microsoft with some business partners. How the Apple ecosystem syncs with Apple Storage seamlessly between devices is astonishing. There is no single answer. Just that currently it is mandatory.

It is very good and useful to have one or more options for cloud storage. It is certainly necessary to know which is your main cloud storage, but it is desirable and good to have at least one additional one for some important documents for faster searching of targeted documents on the way.

I prefer iCloud since Apple moto is privacy. I do not trust Google Drive or OneDrive since they are profiling you and keep stuff.

I have found cloud storage to be an indispensable asset for efficient data analysis. The ability to store and access data files online through services like Google Drive, Dropbox, or OneDrive offers unparalleled convenience and flexibility. By synchronizing data across multiple devices, users can seamlessly access their files from anywhere with an internet connection.This enhances productivity and enables real-time collaboration and data sharing with team members or clients. For instance, platforms like Google Sheets facilitate online spreadsheet creation and editing, fostering seamless teamwork.Cloud storage has undoubtedly revolutionized the way we manage and utilize data, making it an essential tool in the mobile communication landscape.

Microsoft OneDrive: This service is best for Windows users and offers seamless integration with Microsoft Office. It also provides 5 GB of free storage. Google Drive: This service is best for Google Workspace users and offers 15 GB of free storage. It also provides seamless integration with Google Docs, Sheets, and Slides. Dropbox: This service is best for those who need to share large files frequently. It offers 2 GB of free storage and has a user-friendly interface. There are many other cloud storage services available, each with its own unique features and pricing plans. You can compare the top cloud storage services and file-sharing services.

My experience of Data Visualization comes from some of the companies i have worked in my career and the key thing to think of is: 1. The transformation of data: Data visualization is pivotal in converting complex data sets into more understandable and interactive formats like graphs, charts, maps, and dashboards. One company that I work with is RAIN.GLOBAL that has worked a lot in this area to support visualization for energy efficiencies for TowerCo and Communication Service Providers. 2. Revealing Insights: The effective data visualization techniques can uncover hidden patterns, trends, and insights within the data that might not be immediately apparent from raw data and this is critical to use if you want to have actionable insights.

Data visualization plays a crucial role in transforming data into meaningful insights. It allows us to present complex information in a visually appealing and easily understandable format. By using powerful data visualization tools like Power BI, Tableau, or Qlik Sense, we can create interactive dashboards, graphs, and charts that help reveal patterns and trends within the data. These visuals facilitate better analysis and enhance communication by enabling us to present our findings in a compelling manner. The ability to connect to various data sources, customize visuals, and share them online or offline makes these mobile apps invaluable for effective data analysis and communication.

Data visualization is taking a quantum leap into the future with the emergence of new-age tools! ?? From interactive dashboards to immersive 3D visualizations, these cutting-edge tools are revolutionizing how we explore and understand data. ??? With platforms like Tableau, Power BI, and Plotly, we're not just visualizing data—we're experiencing it in a whole new dimension.

Data visualization is a powerful tool that can help you to better understand your data and communicate your findings to others. It involves transforming raw data into visual representations such as graphs, charts, maps, or dashboards, which can reveal patterns, trends, and insights in a way that is easy to understand. Data visualization is particularly useful when working with large datasets, as it can help you to identify trends and patterns that might not be immediately apparent when looking at the raw data. It can also help you to identify outliers and anomalies, which can be important for understanding the underlying data. There are many different tools and software available for creating data visualizations.

I’ve done a lot of work on charts and graphs, which makes things easier and faster, you can analyze them to find what you need. And you can show it to your manager quite well

Data analysis on the go is conceptually blended with MATLAB mobile With its rich libraries and GUI it’s the preferred choice for data analysis

Data analysis apps like RStudio, Pythonista, and MATLAB Mobile are essential tools for advanced data analysis in the mobile communication industry. They offer statistical analysis, predictive modeling, and machine learning capabilities using programming languages like R, Python, or MATLAB. These apps provide access to specialized libraries, saving time and effort. They also enable seamless interaction with data and results, enhancing the user experience. These apps revolutionize complex data analysis in mobile communication by empowering users with advanced capabilities and intuitive data interaction.

MATLAB Mobile is a great tool for data analysis on the go. It allows you to stream data from your mobile device sensors to your MATLAB Mobile, MATLAB Online, or a MATLAB session on a desktop or laptop computer. You can perform MATLAB operations on the sensor data in MATLAB, MATLAB Mobile, or MATLAB Online, which provide the MATLAB command-line interface with the ability to interact with device sensors. MATLAB Mobile also allows you to access the camera and acquire images from your mobile device in MATLAB, MATLAB Mobile, and MATLAB Online. You can set camera properties including resolution, autofocus, and flash MATLAB has a rich library of functions and toolboxes that are useful for data analysis.

Excel. Microsoft Excel is the most common tool used for manipulating spreadsheets and building analyses., with the built-in pivot tables being the most popular analytic tools

Data analysis apps for mobile communications provides real-time analytics, network performance metrics, KPI monitoring and generate insights. For example use Tableau Mobile or Microsoft Power BI for on-the-go analytics

One thing I've found helpful is utilizing data collection methods to gather and organize data from various sources. This allows for the enrichment of data sets and improves data quality and accuracy. There are several mobile apps available, such as SurveyMonkey, Google Forms, or ODK Collect, that facilitate the creation and distribution of surveys or forms. These apps can be used both online and offline, enabling the collection of responses from the target audience. Additionally, they offer the functionality to analyze and export data to other platforms, enhancing the overall data analysis process.

In my experience: - Network optimization with detail of mobile network performance, such as signal quality, coverage, speed, latency and others. Problem identification and network optimization. - Troubleshooting to identify and resolve issues such as dropped calls, slow connections or service interruptions, and take prompt corrective action. - Service quality improvement: data collection and analysis enables monitoring of service quality to set performance targets. - Post-processing supports strategic decision making, identifying trends, behavioral patterns and improvement opportunities for better infrastructure decision making and implementation of new technologies. - Personalize services to improve user experience and brand loyalty.

When analyzing data on the go, essential mobile tools include cloud storage for seamless file access, data visualization apps like Power BI for transforming data into visuals, and advanced analysis with apps like RStudio. Data collection tools like SurveyMonkey aid in efficient data gathering, while prioritizing data security with apps like Signal ensures protection. Collaboration tools like Slack foster teamwork. Consider these for effective mobile data analysis.

For sensitive files use an encryption tool like Encrypto or PGP. Send the shared key with your recipient using a secured channel like Signal (not WhatsApp) lol !

Data Collaboration stands out for me at Digicel Business. It’s more than sharing files; it’s about empowering teams to work together seamlessly, regardless of location. This tool has revolutionized our approach, fostering a culture of innovation and efficiency that drives us forward. In the fast-paced telecom world, these tools aren't just useful; they are essential.

If your data collection can be managed with a a smartphone app, possibly connecting to the actual sensors with BLE, you have the advantage of a huge installed base. For collecting data directly from embedded systems I would go for LTE cat-1bis, which has global coverage should have enough data throughput for most use cases. If data rates are low and global coverage is not needed a cheaper solution is NBIoT, also in the LTE technology family.

I could see webex, teams and even skype for communicating with specialists who belong to organizations where such tools are quite common and usually their use is mandatory. finally microsoft office or wps etc may be needed for presentation of the outcome of the analysis. the receivers may not be familiar with the tools mentioned above.

Todo va a depender del nivel de maduración digital que tenga la empresa. Power Bi sigue siendo por naturaleza la herramienta más utilizada para el análisis de datos y la toma de decisiones. Ahora bien la posibilidad de escalar es altísima ya que se puede incorporar herramientas de inteligencia artificial que de acuerdo a la necesidad de información pueda recabar información y realizar y pre análisis de la analítica requerida. Considero que los espacios de colaboración para esto son críticos ya que el poder de análisis y la toma de decisiones no se basaría en el pre concepto de una sola persona sino de toda una organización inclusive.