Data. Consulting. Analytics. Technology.

Tag: dashboards

Business Intelligence

Smart City, Smart People, Smart Data

Smart City, Smart People, Smart Data

Creating a smart city is based on concepts of innovation, technology, sustainability and accessibility ensuring economic progress as well as a higher quality of life. This is opening an infinite number of opportunities to become more efficient in both public and private management. It means that  both the public sector, as well as the private (all types of business)  sector have to be prepared to express their ambitions collaboratively about what they want to achieve in the future. 

Democratisation of technology has meant that people are much more demanding, informed, über-connected and multi-channel. With the advent of new technologies in particular Internet of things, new business models are emerging to  build solutions that increase or improve  the citizens’ quality of life. from optimising public transport routes to using smart garbage bins to track litter habits.

Whilst the deployment  of smart cities involve several innovative technologies to facilitate sustainable urban spaces, the concept is still vague and open.  The ‘smart’ capabilities need to be operational and measurable. In order to evaluate how ‘smart’ is a smart city, robust data management and analysis is required.

This entails very close collaboration between both public and private sectors to share and analyse the vast amount of data being generated by new technologies. There are a billion places to gather data, and more tools are coming to market to help collect as much of it as possible.

The ability to share vital information in real time would enable businesses operating both in the private and public sector to develop powerful hardware systems  and software solutions;  that not only support automation but provide the ‘smart’ capabilities of a city and its infrastructure. Today, there’s an assortment of technologies being used to handle various characteristics, such as high volume, data location, and a variety of data source types. The collection of crucial data from any kind of source, such as the own city’s sensors, participatory sensing (for instance, sensors integrated in citizens’ smartphones), would enable the compilation of information about people and vehicle traffic, parking, environmental values, waste generated, energy consumption and healthcare etc.  for the smart functioning of the city’s basic services.

It’s easier said than done one is tempted to say. Whatever the hype, whether artificial intelligence, machine learning or automation, it must start with data. Data is vital for smart cities technology.

First and foremost sound and mature data management practices  need to be in place. Technology alone is not sufficient to build a smart city. Competent human intelligence is also part of the equation to complete this:  Employees need to be comfortable analyzing and making decisions with data. Not only should the data analytics platform be robust, the team’s responsible for it must have a good mix of skills. The tecchies and fuzzies of this world will drive the vision of the Smart City not the traditional analysts.

“Finding solutions to our greatest problems requires an understanding of human context as well as of code; it requires both ethics and data, both deep thinking people and Deep Learning AI, both human and machine; it requires us to question implicit biases in our algorithms and inquire deeply into not just how we build, but why we build and what we seek to improve.” * (Scot Harley )

The essential question in the continuously growing amount of data volumes is how to make practical use of these volumes and without analytics, interpretation and algorithms it just isn’t possible. Advanced analytics has emerged as a critical component of modern analytics architecture, with companies turning to statistics, predictive algorithms, and machine learning to maximize the value of very large data sets. Without having to examine every dimension and variation in the data manually, people are automatically guided to relevant insights and alerted to data points that are worth exploring. The use of AI-driven smart data for customer analysis, fraud detection, market analysis, and compliance is becoming a reality to uncover insights hidden in data.

Investing in a strong modern analytics platform leverages the partnership between Business and  IT . When business users are given tools to analyze data on their own, they are free to answer questions on the fly, knowing they can trust the data itself. This leads to accurate, agile reports and dashboards and one single version of truth. And IT, free from dashboard and change requests, can finally prioritize the data itself: safeguarding data governance and security, ensuring data accuracy, and establishing the most efficient pipelines for collecting, processing, and storing data.

Adapting to a scenario that is extremely technologically, economically and socially dynamic is the lynchpin of  development and helps to drive smart systems geared towards improving integration and interaction of the smart citizen.

When data is approached intelligently to generate insights into how the  tech systems are performing it is only then that efficiencies and savings could be measured across all strategic elements of Smart Cities -enterprise competitiveness, mobility, urbanism, energy, water, waste recycling, security, culture and healthcare.

Self-service Analytics

Manage your Hospitality using Tableau Software

Data and analytics are playing an increasingly critical role in hotel and leisure operators’ understanding of their customers’ behaviour, so that swift actions can be taken to really satisfy their needs and wants.

At the same time, hotel operators have multiple datasets lying in various locations – customer profiles, customer feedback, occupancy rates, F&B sales etc. – creating data silos, from which the fullest potential cannot be tapped until they are integrated to gain a single version of truth.

Your teams could use Tableau to develop weekly and monthly reports that they could share with the entire company. The reports could feature sales figures and updates from top management and country managers, marketing and financial data, along with other growth updates. The comprehensive dashboards make sharing complex information with the rest of the company a much easier task.

With weekly reporting that details KPIs and shows how booking patterns are changing, details on revenue, commission and conversion rates but to name a few, allows you to extract the best insights for the team.

Tableau helps you stay competitive by making the time to develop and deliver insightful analysis and reports significantly shorter.

A business, which is highly metric-driven, is optimized with Tableau’s rapid-fire data analytics and drag-and-drop functions as period-on-period metric can be compared.

Tableau is a powerful tool because of its cross-platform adaptability. Tableau’s beautiful dashboards can be mobile-optimized, which makes it easy for everyone to access the findings even on the go. Tableau basically has the power to give you any insights you are looking for from the data that you can get your hands on.

Tableau can be a huge game-changer. So instead of having to wait for something to already happen and then try to figure out why it happened, you can now proactively look out and see what’s going to happen before it happens and then prepare for that or maybe change it.

 

Self-service Analytics

Track profit, loss with an intuitive CFO dashboard

This CFO dashboard combines complex profit-and-loss data into one page that’s anything but. The top two views provide an overall picture of quarterly and yearly performance over the past three years. The views include key financial measures such as net sales, net profit, and net profit margin. Whether you want to view your numbers according to region, channel, customer segment, or product category, the results are right at your fingertips.

Click on the link below and be amazed by this dashboard . It’s just a click  away!!

https://www.tableau.com/solutions/workbook/cfos-overview-business

 

Happy to have a chat with you to share ideas, discuss opportunities or even prepare a demo for you . Contact us on info@businesslab.mu.

Self-service Analytics

4 ways visual analytics can be additive to improve financial analysis

What if financial professionals had a faster way to complete all of their reporting and scale ad-hoc question and answer cycles? What if the finance department could improve the communication of insights to the entire enterprise—even within existing tech stacks, and large disparate databases?

Modern financial departments are adding self-service, visual analytics to their existing processes to deliver richer and more actionable insights to the business faster.

4 ways visual analytics can be additive to improve financial analysis and save significant time across many use cases and finance teams:

  1. Unify and use all of your data
  2. Scale and repeat analysis faster
  3. Interactive, ad-hoc analytics reveal data outliers
  4. Improve organisational communication if insights

 

1.Unify and use all of your data

Regardless of the size of your organization, there’s financial data everywhere—and a lot of it. Whether you want to analyze live enterprise resource planning (ERP) data living in a warehouse, or transactional data living in the cloud, or still dump HR and CRM data into different spreadsheets, you can combine any and all of it within a single, visual analytics platform, and blend it on a common field to see more accurate, holistic views of your data.

Once you have your data connected and unified with a visual analytics platform, not only will you be able to select specific data sets on-the-fly, and choose which metrics to work with, you’ll spend way more time doing deeper analysis in a visual setting.

 

2.Scale and repeat analysis faster

Whether you’ve been filling your spreadsheets to the breaking point, working with smaller data sets, or running sophisticated macros and calculations in spreadsheets, you’re often left waiting and miserable. You just need to iterate your existing analysis more quickly— you need to be able to ask and answer your data questions without having to start over every time. Once you’ve

unified your data, you’re ready to take your analysis to the next level with visual analytics.

 

3.Interactive, ad-hoc analytics reveal data outliers

Visual analytics are not chart wizards—they’re interactive, can connect to live data sources, and offer an ever-changing analysis of what’s happening now, not last week or last month. Visual analytics can take static reports and turn them into automated and interactive dashboards that anyone can access for the most accurate insights at any time. Everyone in the finance department will spend less time dealing with broken formulas, human error, and more time interacting with data in a dynamic way to explore and reveal critical insights coming from data outliers.

 

4.Improve organisational communication of insights

With visual and interactive dashboards, collaboration is built in as an integral step in the organization’s cycle of analytics. There are no additional configurations or add-ons required to share or collaborate with data, and because users can ask and answer their own questions directly in the dashboard, there are fewer redundant emails and requests to run more numbers. Finance users can simply publish and share dashboards online, to a server, or directly with the people with whom they want to collaborate, and they can immediately see how often reports are being viewed and used. And with live data connections, reports aren’t instantly out of date.

 

Source:Tableau Software