Quandatics Australia

16/05/2022

Businesses today swim in data. It describes many aspects of the business: finance, sales, customer, development, production, supply-chain, human resources, etc.

Data gives us clues and insights into foreseeable problems and sheds light on potential solutions and improvements.

Yet most businesses falter when faced with the large volumes of data they have gathered over time -

Where do they begin? How are they to sift through the inhuman amounts of numbers quickly enough for them to be useful?

In comes the Data Dashboard...

We use a data dashboard to transform raw data into a useful representation that is interactive and visually intuitive.

A data dashboard reveals to users a comprehensive overview of key business aspects in terms of key performance indicators (KPI) which helps foster growth and further improvement.

By transforming raw data into measurable indicators, data dashboards can offer consistent performance benchmarking which drives action which align with your business goals, aims and strategies.

TLDR version:

𝗪𝗵𝗮𝘁 𝗜𝘀 𝗧𝗵𝗲 𝗣𝘂𝗿𝗽𝗼𝘀𝗲 𝗢𝗳 𝗔 𝗗𝗮𝘁𝗮 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱?
A data dashboard could answer business-related questions based on your individual goals, objectives, and strategies. It fulfills these purposes:

✅ Tracking essential business metrics
✅ Reporting data to stakeholders
✅ Monitoring business intelligence initiatives
✅ Visualizing operational data both at a high level and broken down

Check out the datapine blog which offers beautiful dashboard templates tailored for a wide range of business functions:

Source: Bernardita Calzon
(https://www.datapine.com/blog/data-dashboards-definition-examples-templates/)

25/04/2022

𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆: 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗧𝘆𝗽𝗲𝘀 𝗼𝗳 𝗖𝘆𝗯𝗲𝗿 𝗧𝗵𝗿𝗲𝗮𝘁𝘀

☀️ 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗰𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆?
Cybersecurity is the practice of securing critical systems and sensitive information from digital threats. Cybersecurity measures, also known as information technology (IT) security, are intended to combat threats to networked systems and applications, whether they originate within or outside of a company.

Customers' personally identifiable information (PII) — names, addresses, national identification numbers are targeted by cybercriminals, who sell these records in underground digital marketplaces. Compromised PII often results in a loss of consumer confidence, regulatory penalties, and even legal action.

☀️ 𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝗰𝗼𝗺𝗺𝗼𝗻 𝗰𝘆𝗯𝗲𝗿 𝘁𝗵𝗿𝗲𝗮𝘁𝘀?
✅ Malware
Malware refers to malicious software types such as worms, viruses, Trojans, and spyware that allow unauthorized access to computer systems or even cause damage to it.

✅ Phishing
Phishing scams involve emails or text messages that pretend to be from a legitimate company and request sensitive information such as credit card details or login information.

✅ Insider threats
Insider threats comprise current or former employees, business partners, contractors, or anyone who has had access to systems or networks in the past if they abuse their access permissions.

✅ Man-in-the-middle attacks
Man-in-the-middle attacks, as known as eavesdropping attack, occurs when a cybercriminal intercepts and transmits messages between two parties in order to steal data.

Source: StealthLabs and IBM
(https://www.ibm.com/my-en/topics/cybersecurity)

🔥 Wish to learn more about cybersecurity? Join our 𝗙𝗿𝗲𝗲 𝗪𝗲𝗯𝗶𝗻𝗮𝗿: 𝗔𝘁𝘁𝗮𝗰𝗸 𝗦𝘂𝗿𝗳𝗮𝗰𝗲 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 – 𝗧𝗵𝗲 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 and register now to grab your free seat:
https://academy.quandatics.com/.../attack-surface.../...

22/04/2022

has unleased to the public, pushing into a brave new world ripe for new and creative use cases and possibilities.

What would you do with GPT-3? 🤖

https://www.analyticsinsight.net/gpt-3-the-best-ai-tool-for-marketing-copy-generation-in-2022/

Businesses must look out for GPT-3 as the top AI tool for using in marketing copy generation. Leveraging artificial intelligence for marketing copy is necessary to retain customers in this global tech market.

19/04/2022

Unstructured data has become increasingly relevant in the business intelligence landscape as they are a rich data source for AI and to rely upon. Legacy data infrastructure will no longer be sufficient.

Here are signs that you need to pursue a data modernization strategy for unstructured :
- Disagreements about who has the right data
- Finger pointing and anecdote-driven decision-making
- Skyrocketing storage costs and complexity
- Expensive, long, and slow backups and restores
- Spiraling cloud costs
- Frustrated data consumers who cannot access and analyze the right data at the right time in the right format

In this Q&A, Kumar Goswami, CEO of Komprise, answers questions about data modernization strategies and trends.

14/04/2022

You've heard of running on impressively large computing clusters, on the cloud. And then there's .

TinyML are machine learning models optimised for devices which are limited in terms of memory, processing, power and/or connectivity.

But why not just rely on the cloud?

Well, there are real use cases where cloud may not be suitable:
- semi-autonomous robots rely on low-latency decision-making without internet
- healthcare data which are subject to privacy and regulations
- the billions low-powered embedded sensors

However, there are real challenges faced with TinyML.

Unlike the cloud with its practically limitless resources, most are limited to a few hundred kiB memory and a few MiB of storage.

Researchers overcome the constraints with strategies such as pruning input insignificant to output, or to reduce the model input size.

And then there's , which breaks down computation into more manageable patches.

With time we can expect an emergence of intelligent devices powered by TinyML as it finds its way into countless microcontrollers in homes, offices, factories, farms, etc. enhancing embedded systems like never before. :)

IBM and MIT have created a new deep learning technique that can run CNNs on low-power, low-memory microcontrollers.

10/04/2022

On what days do people demand more pizzas?
How early can we give our suppliers heads-up?
How can we reduce food waste?

How did the data science team at tackle the challenge of a lean and mean (and cheesy) pizza supply chain?

A slice of the story by Ryan Frederick 🍕

Ryan Frederick of Dominos talks about how his data science team worked through a complex time series forecasting exercise and scaled R-based time models.

07/04/2022

Although AI struggle through common-sense tasks in the real world, it is adept at crunching data volumes too big for humans to ever hope to sift through.

This is why AI is poised to become a valuable decision-support aid to its human overlords. (At least for now. 🤖)

Bonus: it is capable of "learning" over time!

So- what does this mean for businesses of today?


https://www.businessnewsdaily.com/9402-artificial-intelligence-business-trends.html

06/04/2022

🤔 Would you conduct business with someone who can't be trusted to protect your data?

Explore more about data security for your organization:
https://www.ibm.com/my-en/topics/data-security

Find out how data security helps protect digital information from unauthorized access, corruption, or theft throughout its entire lifecycle.

04/04/2022

It pays to invest in loyalty.

Let's face it -- gaining new customers can be a slow and painful undertaking. No one wants to see customers carry their businesses elsewhere. 👋🏻

Perhaps our can help us understand customers better, and inform successful strategies towards retaining them?

Come join our hands-on workshop! 🤖


https://www.facebook.com/events/539112557857023

01/04/2022

Has encouraged novel ways of optimising ?

Is adoption a legitimate strategy?

https://www.cio.com/native-link/digital-futures/collection/be-digital-time-to-think-at-scale/article/innovation-in-the-wake-of-covid-19-businesses-turn-to-the-cloud

In pandemic’s aftermath, IT leaders are looking to expand their reliance on the cloud as a foundation for digital transformation.

31/03/2022

𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀

❓ 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲?
Data science is the process of building, cleaning, and structuring datasets to analyze and extract meaning. It is a multidisciplinary approach to obtaining actionable insights from the massive and ever-increasing volumes of data collected and created by organizations.

Data science comprises preparing data for analysis and processing, undertaking advanced data analysis, and presenting the results to reveal patterns and allow stakeholders to make informed conclusions.

❓ 𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲?
✅ Gain customer insights
Data about your consumers can reveal information about their behaviors, demographics, interests, aspirations, and so forth. Hence, a foundational understanding of data science can assist marketers in identifying the market trends and yet, developing more suitable marketing efforts on the target market.

✅ Enhance security
Data science could enhance a company's security and secure sensitive information. For instance, banks deploy complex machine-learning algorithms to detect fraud based on deviations from a user's regular financial actions. Due to the vast volume of data created every day, these algorithms can detect fraud faster and more accurately than humans.

✅ Streamline manufacturing
High-volume data collection from manufacturing processes can be performed by manufacturing machines. When the volume of data collected is too large for a human to manually evaluate, an algorithm can be created to clean, sort, and interpret it fast and accurately in order to gain insights. By utilizing data science, organizations manage to cut costs and produce more goods.

✅ Inform Internal Finances
The finance team of an organization can use data science to develop reports, generate forecasts, and evaluate financial patterns. Data about a company's cash flows, assets, and debts are constantly collected, which financial analysts can use to discover trends in financial growth or decrease manually or algorithmically.

✅ Predict Future Market Trends
Data collection and analysis on a larger scale can help marketers recognize emerging trends in the market. Tracking purchase data, celebrities, influencers, and search engine results can all be used to determine which products consumers are interested in.

Source: Catherine Cote
(https://online.hbs.edu/blog/post/what-is-data-science)

29/03/2022

𝗙𝗿𝗲𝗲 𝗪𝗲𝗯𝗶𝗻𝗮𝗿: 𝗔𝘁𝘁𝗮𝗰𝗸 𝗦𝘂𝗿𝗳𝗮𝗰𝗲 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 – 𝗧𝗵𝗲 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆
🔑 What is the importance of effective cybersecurity?
🔑 What can organisations do about cybersecurity threats?

Join our webinar sharing session on 𝟮𝟭𝘀𝘁 𝗔𝗽𝗿𝗶𝗹 𝟮𝟬𝟮𝟮,𝟭𝟬:𝟯𝟬𝗮𝗺 (𝗚𝗠𝗧+𝟴) together with our speaker, 𝗠𝗶𝗰𝗵𝗮𝗲𝗹 𝗧𝗮𝗻 from CyCognito to explore more about effective cybersecurity for your organizations. In this session, we will talk about what is External Attack Surface Management, why CyCognito EASM platform can help you to manage your Attack Surface effectively, easily with automation and integration to your existing adjacent security portfolio. Let’s listen to what expert says to protect your organization effectively from critical security risks 🔐

📍 Reserve your FREE seat now at:
https://academy.quandatics.com/course/attack-surface-visibility-the-foundation-of-effective-cybersecurity