GIVING-UP IS TOO EASY:

Life is too hard not only for us, those who survived in the tough times. They just decided not to give up. They knew very well, there is no progress. But they started to keep moving a bit by bit. More often, they decided to a standstill.

They do self-talk with two questions:

  1. I never go down fighting.
  2. I never give up.

Giving up is such a comfortable option in life or profession. It is easy to give up. Once, you started learning not to give up. Once you started to fight back. There will be no second thought for giving up. It’s all about your instinct/mindset decides to fight back.

When things started plummeting, they console themselves and they say we are in the messy middle. So, we have to look at the vantage point (an optimistic view).

It is good to a standstill with holding dreams and desires. Rather than simply giving up. If you pause for a moment in the hard times. You can lean back and have a pep-talk with deeper questions.

What is my regret?

How can I bounce and in these hard times?

What are the pitfalls from my side?

What is my complete weakness?

Where are the possibilities to grow?

What’re the resources do I have?

To the extent, how can I survive?

These are relevant questions for not to give up.

It is better to wait for success, rather than quitting in the present.

It’s better to a standstill, rather than losing hope.

It’s better to look into the possibility of progress, rather than holding regrets.

Giving-up is too easy.

 

With respect.

 

VALUABLE LESSONS: 9 IN-DEMAND SKILLS THAT SHOULD BE MANDATORY IN SCHOOL:

The first step is to equip the students from school itself. Here, I’m not contradicting or making a controversial statement with college students or if a fresher joined in organizations or any experienced peoples.

I will motivate and convey values to anyone. Categorically, age is just a number. Any human can learn skills at any age. You can learn/acquire any skills until your last breath.

The point is, to me as an upcoming professor, it would be better if children can learn possibly within the school. So, this is one of the 9 In-demand skills that are highly required to engage.

All these nine skills are absolutely required. But the first one must. Money management is the most important skill. They must know how to save and spend. Even more, how to invest and diversify too. Rather than just the motto of earning money/making passive income/even building fortunate too.

I personally gonna be the volunteer to teach school students with these 9 In-demand skills. I had seen a few similar posts in Instagram too. Although, my thinking started getting a clear picture and rises questions within myself too.

  • Why school students aren’t getting many possibilities in these kinds of skills?
  • What will be the impact?

If these skills are learned. I promise and believe, their career gonna be massive.

This impactful pic got it from Twitter. I’m gonna share the source link down below. Please visit further.

Here it is.

EdcRAVmXgAACCgT

 

SOURCE: https://twitter.com/larrykim/status/1285514917831901186

With respect.

 

 

 

 

FAIR VIEW ABOUT DATA CENTRE:

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The companies/organization who are maintaining data centres are an absolutely crucial challenge. When I started studying the data centres, I had seen Microsoft, Google, Facebook and Day in the life of a data centre videos. Apart from it, I went through very few articles.

Interestingly, the security level seems enormous. Precisely, I saw a video on Google Data Center Security: six Layers Deep. Technicians look notably, professionals. Because in a Day in a life of data centre video they review and change several hard drives and doing repairs shows their dedications.

Apart from watching videos, if I had an opportunity to visit any data centre, I will go. I would argue, it doesn’t matter which data centre you have a visit. It all matters with the experience you are gonna gain in the data centre by looking at the way they work.

Finally, the investment made to build the data centre is gigantic. With humility, we must pay respect to the professionals who are in the data centre.

I’m gonna combine the two articles about the data centre. I would say those two says fair view about the data centre.

I’m gonna paste the source link down below. I sincerely encourage you all to visit further.

What Is a Data Center

At its simplest, a data center is a physical facility that organizations use to house their critical applications and data. A data center’s design is based on a network of computing and storage resources that enable the delivery of shared applications and data. The key components of a data center design include routers, switches, firewalls, storage systems, servers, and application-delivery controllers.

What defines a modern data center?

Modern data centers are very different than they were just a short time ago. Infrastructure has shifted from traditional on-premises physical servers to virtual networks that support applications and workloads across pools of physical infrastructure and into a multicloud environment.

In this era, data exists and is connected across multiple data centers, the edge, and public and private clouds. The data center must be able to communicate across these multiple sites, both on-premises and in the cloud. Even the public cloud is a collection of data centers. When applications are hosted in the cloud, they are using data center resources from the cloud provider.

Why are data centers important to business?

In the world of enterprise IT, data centers are designed to support business applications and activities that include:

  • Email and file sharing
  • Productivity applications
  • Customer relationship management (CRM)
  • Enterprise resource planning (ERP) and databases
  • Big data, artificial intelligence, and machine learning
  • Virtual desktops, communications and collaboration services

What are the core components of a data center?

Data center design includes routers, switches, firewalls, storage systems, servers, and application delivery controllers. Because these components store and manage business-critical data and applications, data center security is critical in data center design. Together, they provide:

Network infrastructure. This connects servers (physical and virtualized), data center services, storage, and external connectivity to end-user locations.

Storage infrastructure. Data is the fuel of the modern data center. Storage systems are used to hold this valuable commodity.

Computing resources. Applications are the engines of a data center. These servers provide the processing, memory, local storage, and network connectivity that drive applications.

How do data centers operate?

Data center services are typically deployed to protect the performance and integrity of the core data center components.

Network security appliances. These include firewall and intrusion protection to safeguard the data center.

Application delivery assurance. To maintain application performance, these mechanisms provide application resiliency and availability via automatic failover and load balancing.

What is in a data center facility?

Data center components require significant infrastructure to support the center’s hardware and software. These include power subsystems, uninterruptible power supplies (UPS), ventilation, cooling systems, fire suppression, backup generators, and connections to external networks.

What are the standards for data center infrastructure?

The most widely adopted standard for data center design and data center infrastructure is ANSI/TIA-942. It includes standards for ANSI/TIA-942-ready certification, which ensures compliance with one of four categories of data center tiers rated for levels of redundancy and fault tolerance.

Tier 1: Basic site infrastructure. A Tier 1 data center offers limited protection against physical events. It has single-capacity components and a single, nonredundant distribution path.

Tier 2: Redundant-capacity component site infrastructure. This data center offers improved protection against physical events. It has redundant-capacity components and a single, nonredundant distribution path.

Tier 3: Concurrently maintainable site infrastructure. This data center protects against virtually all physical events, providing redundant-capacity components and multiple independent distribution paths. Each component can be removed or replaced without disrupting services to end users.

Tier 4: Fault-tolerant site infrastructure. This data center provides the highest levels of fault tolerance and redundancy. Redundant-capacity components and multiple independent distribution paths enable concurrent maintainability and one fault anywhere in the installation without causing downtime.

The Role of the Data Center

Data centers are an integral part of the enterprise, designed to support business applications and provide services such as:

  • Data storage, management, backup and recovery
  • Productivity applications, such as email
  • High-volume e-commerce transactions
  • Powering online gaming communities
  • Big data, machine learning and artificial intelligence

Today, there are reportedly more than 7 million data centers worldwide. Practically every business and government entity builds and maintains its own data center or has access to someone else’s, if not both models. Many options are available today, such as renting servers at a colocation facility, using data center services managed by a third party, or using public cloud-based services from hosts like Amazon, Microsoft, Sony and Google.

The primary elements of a data center break down as follows:

  • Facility – the usable space available for IT equipment. Providing round-the-clock access to information makes data centers some of the world’s most energy-consuming facilities. Design to optimize space and environmental control to keep equipment within specific temperature/humidity ranges are both emphasized.
  • Core components – equipment and software for IT operations and storage of data and applications. These may include storage systems; servers; network infrastructure, such as switches and routers; and various information security elements, such as firewalls.
  • Support infrastructure – equipment contributing to securely sustaining the highest availability possible. The Uptime Institute has defined four tiers of data centers, with availability ranging from 99.671% to 99.995%. Some components for supporting infrastructure include:
    • Uninterruptible Power Sources (UPS) – battery banks, generators and redundant power sources.
    • Environmental control – computer room air conditioners (CRAC); heating, ventilation and air conditioning (HVAC) systems; and exhaust systems.
    • Physical security systems – biometrics and video surveillance systems.
  • Operations staff – personnel available to monitor operations and maintain IT and infrastructure equipment around the clock.

Data centers have evolved significantly in recent years. As enterprise IT needs continue to move toward on-demand services, data center infrastructure has shifted from on-premises servers to virtualized infrastructure that supports workloads across pools of physical infrastructure and multi-cloud environments. There is an expression these days: The modern data center is where your workloads are.

 

SOURCE: https://www.cisco.com/c/en/us/solutions/data-center-virtualization/what-is-a-data-center.html

https://www.paloaltonetworks.com/cyberpedia/what-is-a-data-center

https://www.google.com/about/datacenters/gallery/

 

With respect.

 

 

 

Valuable poetry: Power by Audre Lorde.

ABOUT THE POET:

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A self-described “black, lesbian, mother, warrior, poet,” Audre Lorde dedicated both her life and her creative talent to confronting and addressing injustices of racism, sexism, classism, and homophobia. Lorde was born in New York City to West Indian immigrant parents. She attended Catholic schools before graduating from Hunter High School and published her first poem in Seventeen magazine while still a student there. Of her poetic beginnings Lorde commented in Black Women Writers: “I used to speak in poetry. I would read poems, and I would memorize them. People would say, well what do you think, Audre. What happened to you yesterday? And I would recite a poem and somewhere in that poem would be a line or a feeling I would be sharing. In other words, I literally communicated through poetry. And when I couldn’t find the poems to express the things I was feeling, that’s what started me writing poetry, and that was when I was twelve or thirteen.”

Lorde earned her BA from Hunter College and MLS from Columbia University. She was a librarian in the New York public schools throughout the 1960s. She had two children with her husband, Edward Rollins, a white, gay man, before they divorced in 1970. In 1972, Lorde met her long-time partner, Frances Clayton. She also began teaching as poet-in-residence at Tougaloo College. Her experiences with teaching and pedagogy—as well as her place as a Black, queer woman in white academia—went on to inform her life and work. Indeed, Lorde’s contributions to feminist theory, critical race studies, and queer theory intertwine her personal experiences with broader political aims. Lorde articulated early on the intersections of race, class, and gender in canonical essays such as “The Master’s Tools Will Not Dismantle the Master’s House.”

Lorde’s early collections of poetry include The First Cities (1968), Cables to Rage (1970), and From a Land Where Other People Live (1972), which was nominated for a National Book Award. Later works, including New York Head Shop and Museum (1974), Coal (1976), and The Black Unicorn (1978), included powerful poems of protest. “I have a duty,” Lorde once stated, “to speak the truth as I see it and to share not just my triumphs, not just the things that felt good, but the pain, the intense, often unmitigating pain.” Lorde’s later poems were often assembled from personal journals. Explaining the genesis of “Power,” a poem about the police shooting of a ten-year-old black child, Lorde discussed her feelings when she learned that the officer involved had been acquitted: “A kind of fury rose up in me; the sky turned red. I felt so sick. I felt as if I would drive this car into a wall, into the next person I saw. So I pulled over. I took out my journal just to air some of my fury, to get it out of my fingertips. Those expressed feelings are that poem.”

Her poetry, and “indeed all of her writing,” according to contributor Joan Martin in Black Women Writers (1950-1980): A Critical Evaluation, “rings with passion, sincerity, perception, and depth of feeling.” Concerned with modern society’s tendency to categorize groups of people, Lorde fought the marginalization of such categories as “lesbian” and “black woman.” She was central to many liberation movements and activist circles, including second-wave feminism, civil rights and Black cultural movements, and struggles for GLBQT equality. In particular, Lorde’s poetry is known for the power of its call for social and racial justice, as well as its depictions of queer experience and sexuality. As she told interviewer Charles H. Rowell in Callaloo: “My sexuality is part and parcel of who I am, and my poetry comes from the intersection of me and my worlds… [White, arch-conservative senator] Jesse Helms’s objection to my work is not about obscenity … or even about sex. It is about revolution and change.”

Lorde was a noted prose writer as well as poet. Her account of her struggle to overcome breast cancer and mastectomy, The Cancer Journals (1980), is regarded as a major work of illness narrative. In The Cancer Journals, Lorde confronts the possibility of death. Recounting this personal transformation led Lorde to address the silence surrounding cancer, illness, and the lived experience of women. For example, Lorde explained her decision not to wear a prosthesis after undergoing a mastectomy in the Journals: “Prosthesis offers the empty comfort of ‘Nobody will know the difference.’ But it is that very difference which I wish to affirm, because I have lived it, and survived it, and wish to share that strength with other women. If we are to translate the silence surrounding breast cancer into language and action against this scourge, then the first step is that women with mastectomies must become visible to each other.”

Lorde’s 1982 novel, Zami: A New Spelling of My Name, was described by its publishers as a “biomythography, combining elements of history, biography and myth.” Sister Outsider: Essays and Speeches (1984) collected Lorde’s nonfiction prose and has become a canonical text in Black studies, women’s studies, and queer theory. Another posthumous collection of essays, A Burst of Light (1988), won the National Book Award. The Collected Poems of Audre Lorde was published in 1997.

In 1981 Lorde and fellow writer Barbara Smith founded Kitchen Table: Women of Color Press, which was dedicated to furthering the writings of black feminists. Lorde would also become increasingly concerned over the plight of black women in South Africa under apartheid, creating Sisterhood in Support of Sisters in South Africa and remaining an active voice on behalf of these women throughout the remainder of her life. Lorde addressed her concerns to not only the United States but the world, encouraging a celebration of the differences that society instead used as tools of isolation. As Allison Kimmich noted in Feminist Writers, “Throughout all of Audre Lorde’s writing, both nonfiction and fiction, a single theme surfaces repeatedly. The black lesbian feminist poet activist reminds her readers that they ignore differences among people at their peril … Instead, Lorde suggests, differences in race or class must serve as a ‘reason for celebration and growth.’”

Lorde’s honors and awards included a fellowship from the National Endowment for the Arts. A professor of English at John Jay College and Hunter College, Lorde was poet laureate of New York from 1991-1992. Warrior Poet (2006), by Alexis De Veaux, is the first full-length biography of Audre Lorde.

POWER.

The difference between poetry and rhetoric

is being ready to kill

yourself

instead of your children.

 

I am trapped on a desert of raw gunshot wounds

and a dead child dragging his shattered black

face off the edge of my sleep

blood from his punctured cheeks and shoulders

is the only liquid for miles

and my stomach

churns at the imagined taste while

my mouth splits into dry lips

without loyalty or reason

thirsting for the wetness of his blood

as it sinks into the whiteness

of the desert where I am lost

without imagery or magic

trying to make power out of hatred and destruction

trying to heal my dying son with kisses

only the sun will bleach his bones quicker.

 

A policeman who shot down a ten year old in Queens

stood over the boy with his cop shoes in childish blood

and a voice said “Die you little motherfucker” and

there are tapes to prove it. At his trial

this policeman said in his own defense

“I didn’t notice the size nor nothing else

only the color”. And

there are tapes to prove that, too.

 

Today that 37 year old white man

with 13 years of police forcing

was set free

by eleven white men who said they were satisfied

justice had been done

and one Black Woman who said

“They convinced me” meaning

they had dragged her 4’10” black Woman’s frame

over the hot coals

of four centuries of white male approval

until she let go

the first real power she ever had

and lined her own womb with cement

to make a graveyard for our children.

 

I have not been able to touch the destruction

within me.

But unless I learn to use

the difference between poetry and rhetoric

my power too will run corrupt as poisonous mold

or lie limp and useless as an unconnected wire

and one day I will take my teenaged plug

and connect it to the nearest socket

raping an 85 year old white woman

who is somebody’s mother

and as I beat her senseless and set a torch to her bed

a greek chorus will be singing in 3/4 time

“Poor thing. She never hurt a soul. What beasts they are.”

 

Audre Lorde, “Power” from The Collected Poems of Audre Lorde. Copyright © 1978 by Audre Lorde.  Used by permission of W. W. Norton & Company, Inc.

Source: The Collected Poems of Audre Lorde (W. W. Norton and Company Inc., 1997)

 

Source: https://www.poetryfoundation.org/poems/53918/power-56d233adafeb3

With respect.

 

MY NEW DOMAIN: rationalewriter.in/

It took me more than a while to register a domain. Quite honestly, I was struggling financially. But I have a purpose to write. I was intent to write. From my first post, until today I have no regrets to write without domain. It is all about writing matters to me.

I have no idea when this domain name arose to me as a “Rationale writer”. I thought innovative. The word rationale mean “the fundamental reason or logic behind something, the justification behind something”.

I started having self-talk, whether this word “Rationale” applies to my every post. I scrolled down every post by post. Whenever I write a blog post, I write a reason behind it. I see a cause. Moreover, I could able to write why am I writing or sharing. Sometimes not. Whether pics or books I have a reason to post it. My each and every post had been posted purposely for a right cause and impact for an reader Even more, I have a vantage point too.

I have a second thought, I could seek help from my brother regarding domain. We were started discussing what’s going on so far from my blog. Categorically, I said to him. I got a new name for my blog. I should not waste. That’s it. I said, I don’t know how new it is. I need your help. Let’s type this domain and let’s see. Finally, things got settled.

Finally, I said to him. There is a reason behind to register a domain immediately because I have a new thought, I don’t know how it is. I would say “Universal Law of attraction”. When you are deliberately looking for something, the universe will open doors for you.

Still quite happy, often too. I’m still thinking writing is the journey. Domain seems fine. Let’s work and write rationally than ever before. Let’s write for a reason/logic. Let’s accept the challenge to write.

 

With respect.

 

Valuable lessons: The importance of data quality: A sustainable approach By SAS Insights staff.

Quality matters with everything. When it comes to data, we must learn to pay huge attention. I think we do more than adequate when it comes to the quantity of data. But the quality the question mark arises here. Because once you started concentrating more on the quality of data as equal to the quantity of data. The possibility of output would be successive. If the quality fails at some point, the better option you could do re-work on the data. If sometimes things won’t work as you think, you must move onto the next option of collecting fresh (even primary) data with the quality too.

This is what I supposed to do. Please correct me, if I’m wrong. So far from my experiences in handling data over the last, just 2 years makes to think in this way. Of course, there are enough possibilities to work more on data quality.

When I started learning about data quality. This article comes. The word sustainable approach makes to go farther to read this article and started a new learning curve on data quality. I love the word sustainability. Being an M.A Economics student, I started understanding the word “Sustainability”.

I’m gonna paste the source link down below. I sincerely encourage you all to visit further.

Nobody likes unpleasant surprises. When it’s time to look objectively at what has been happening in terms of customer activity, business productivity or progress toward targets, everyone wants to be able to trust the reports they’re given. And no one wants to be embarrassed by delivering inaccurate reports, no matter what the underlying reason. In situations like this, the importance of data quality is undisputed.

But how much control does an individual have over the quality of data used in reports? Who is accountable for that data? Who understands where it originated, or how and why it may have been altered? Who gets to write the business rules or the quality standards? There are usually many different business constituents for each set of data, each needing to tell their own story. Do you draw straws to decide who gets to tailor the data to meet their specific business needs? And who gets to say whether the data is wrong?

Of course, there are software tools that can help with data correction and error analysis. But tools alone won’t fix the problem. Business users first need to have a plan to help them identify quality issues, track down underlying sources, develop mechanisms to resolve problems, and then set up a process to monitor and flag any new issues that arise.

Analysts spend from 20 percent to 60 percent of their valuable time trying to understand and fix poor data. Any ROI analysis will take into account the squandered time among analysts across the enterprise who are caught up in these unproductive but necessary activities.

Screenshot_2020-07-18 The importance of data quality A sustainable approach

A sustainable plan

Managing data quality is not necessarily simple. When you consider the data life cycle – from data creation/collection to archival – there are many steps along the way, including:

  • Rules for collecting/creating data.
  • Data quality standards, thresholds and rejection criteria.
  • Data standardization and summarization rules.
  • Data integration rules with other sources of data.
  • Hierarchy management (relationship management).
  • Ongoing triggers to detect outliers during updates.
  • Data correction rules.

An effective, sustainable data quality plan will resonate with business users and should include the following five elements.

Elevate the visibility and importance of data quality

Poor data quality has a significant business cost – in time, effort and accuracy. Quantify the cost of poor data and build a credible business case that demonstrates the negative impact of current data quality problems. Illustrate how data quality affects different parts of the business. This becomes a key part of your justification for why a plan that comprehensively encompasses the importance of data quality is a business imperative.

Formalize decision making through a data governance program

Data correction should not happen in a vacuum, nor should each analyst have his/her own rules for correcting errors. Avoid allowing too many people to make one-off data quality decisions that don’t meet a shared business purpose. Grant authority for developing business rules and standards with a decision-making data governance group that has perspective across business areas. These rules need to be vetted and approved to ensure they’re valid and reusable. Only then should the data quality process be applied.

Document the data quality issues, business rules, standards and policies for data correction

A boss once told me: “If it’s not documented, it didn’t happen.” To battle a fire-fighting culture of data fixes – and to prevent ongoing inefficiencies caused by individuals who correct data inconsistently – you’ll need to document each issue, publish it and communicate the remedy. This encourages users to avoid costly and time-consuming adventures in fixing data in ways that can’t be reused or shared across the organization.

Clarify accountability for data quality

Develop a process whereby business users can report data quality issues and then work with data stewards to research the error’s source and develop a resolution. Relieve business analysts from the burden of researching data quality issues – free them to do their jobs as analysts. Identify data quality specialists, both data stewards and data quality professionals, who are responsible for resolving data quality issues. Those issues can range from root-cause analysis, metadata management and policy definition to documentation and monitoring. This approach – which acknowledges the tremendous importance of data quality – is a huge savings to most organizations.

Applaud your successes

If you’ve crafted your plan carefully, you’ll collect baseline statistics and then measure improvements to data quality over time. Demonstrate the business value to users through your own case studies. The importance of data quality is supreme – better data translates directly into better business value. Be sure you understand how those in different parts of the enterprise measure themselves, and tie the improvements in data quality to improvements in their overall success. Then communicate how to share the value of better data across business areas.

Recognizing the multifaceted nature of questions raised by people with a variety of business interests and perspectives will position you to design a sustainable approach to data quality. As you flesh out details in the data quality plan, include technical experts to work with your business analysts. Together, they can account for the data’s full spectrum of definitions and characteristics while engineering ways to fix and maintain it. The investment will pay off in the short run and for years to come.

 

SOURCE: https://www.sas.com/en_us/insights/articles/data-management/importance-of-data-quality-a-sustainable-approach.html

 

With respect.

 

Valuable lessons: The Importance of Data Literacy by Dataversity.

Foremost when it comes to data, we must learn to collect all the relevant data, then you should read, analyse, segregate, sometimes you have to delete it too. Apart from all, I personally see a few more steps to know and work more in data. When I started thinking about data, I see how to read the data and what to do further. To give a relevant example, when I started learning the R programming language, I collet the datasets to upload in R to Run. In the very initial moment, when I start downloading the dataset, I don’t know what to do. Then I started to keep looking a few datasets and started adjusting the values, filling the blank spaces, and even if I don’t know I delete the particular row or column too.

So here the data literacy plays. I started searching for the importance of data and how to read the data. Then I likely able to know the data literacy through one of this article. Once, if you started knowing how to read and execute the data. The next step would be yours.

I will paste source link down below. I sincerely encourage you all to visit further.

Written by Michelle Knight on March 12, 2019

Walk into a company embracing digital transformation and you’ll find monitors displaying colorful charts and pie graphs decorated with numbers. These dashboards show information about the business meant to assist employees in prioritizing work, seeing new opportunities, and driving efficiency.

An important question remains, though: “How many employees trained on a business’ dashboards know how to use the data and analytics to make them better at their jobs?” asked Jordan Morrow, Global Head of Data Literacy at Qlik, a visual analytics and digital transformation company, in a recent DATAVERSITY® interview. This question has led Morrow on a journey where he finds himself “leading a revolution around teaching people how to use data analytics better in a world taken by a data literacy storm.”

Why should a business care about data literacy when its employees can get by with some basic reports? Morrow responds that leading organizations like Amazon, Facebook, and Netflix go a step beyond by being extremely good at utilizing data, following trends, and analyzing that information. He explained:

“Upon talking to many individuals and organizations from every single continent, except Antarctica, they realize data is one of the best assets to harness. They know the key to success in what has been described as fourth industry revolution requires harnessing data’s power within an organization.”

Morrow firmly believes if an organization does not embrace this data and analytics upheaval, then it will not survive, “because the majority of organizations want in on the action.” However, based on a worldwide study with over 11,000 participants, Morrow found that only one out of every five people felt they were data literate. The results of the study have been published in a Data Literacy Index. “So, people have a software product positioned at their finger-tips where the greater majority do not have the data and analytical skills to use it well,” muses Jordan.

All People Need to Be Data Literate

Think of data literacy as a spectrum of related skills. Raul Bhargava and Catherine D’ignazio from MIT and Emerson College define data literacy as the ability to read, work with, analyze, and argue with data, notes Morrow. He elaborated:

“A data scientist uses the scientific method with data, a career path for a few people. But for organizations that want to utilize data, (1) reading, (2) working with, (3) analyzing, and (4) arguing with data form four key characteristics [of Data Literacy]. People can develop skills in these components to become better in this digital economy.”

For many organizations, nourishing data literacy skills in each employee will be well worth it. Morrow looked at 600+ public companies across the world. This assessment was commissioned with the Wharton School of Business and Qlik. Through statistical analysis, Morrow found that organizations with the top tier of data literacy had a greater enterprise value of three to five percent. This translated to hundreds of millions of dollars of value and better return on equity. Top tier data literate organizations also had a better return on sales and a faster time to market.

Getting Started with Data Literacy

Morrow believes the number one thing impeding data literacy is where to start. He has found “great enthusiasm towards data literacy and a bewilderment on where to begin.” He noted:

“In a world full of hyped up technologies – Big Data, Machine Learning, Artificial Intelligence – the majority of an organization’s employees are not going to tip-toe into these areas. However, most people in a company will use data. They forget this. In addition, people get stuck in an old-school way of doing thing, preventing them from embracing this technological era. A new approach to things is needed to get the DNA to flow through the organization.”

To give people a digital literacy starting place, Morrow has developed a strategy and framework enterprises can adopt. His Adoptive Framework outlines six steps towards a Data Literacy Program, a workforce assessment characterizing data literacy strengths and weaknesses, and suggested roadmaps towards learning data literacy. Morrow is happy to speak with companies that have questions about the framework or that would like help implementing it.

“Companies need to know how to drive a data literacy strategy in house, whether it’s for ten employees or 100,000 employees. This Adoptive Framework that I’ve built does that. The Adoptive Framework describes not how to change a company’s culture, but to evolve a culture towards being more data-informed in its business. I have companies run the framework’s six-step approach every three to six months to bring in more employees. You need to evolve your program.”

Morrow emphasized that his framework builds curiosity, skills on how to ask questions, and the mindset of how to be data literate. He advocates that if everyone were data literate, “fake news” would not exist.

Qlik has helped launch the Data Literacy Project built from this work within data literacy. Morrow directed Qlik’s own Data Literacy Program, developing over the course of two and a half years. Everyone has access to a “nice, robust set of online courses that help [people] understand this world of data and how to use it,” said Morrow. With this program, the Qlik team can to speak to data literacy, not just sell and support a product. Morrow remarked:

“Qlik as a whole strongly believes in bringing resources, materials, and things organizations can use easily to make the technology work. When you think of technology, one of the biggest hindrances in the world is poor adoption. Why? It is not the technology. People don’t know how to uses it, and this impacts access to a world of data.”

Qlik’s work with data literacy emphasizes theory and context so that the user can better understand data. Morrow rarely uses set formulas in his data literacy teaching, as that will do nothing. He travels the world, meeting with customers, prospects, and individuals constantly, speaking often about the Data Literacy Project. This community group links partners like Accenture, Cognizant, Experian, Pluralsight, the Chartered Institute of Marketing, and Data to the People as well as academic thought leaders.

The Data Literacy Project aims to ignite discussion and develop tools to shape a successful data literate society. From this ongoing dialog, industry leaders, Big Data customers, and students can advance their own and spread data literacy. As an open source project, the Data Literacy Project will continue to be developed and foster collaboration. This will get people in the mindset and mentality of using data more and using it better.

Conclusion

Jordan Morrow has seven takeaways for the reader who wishes to continue his or her data literacy journey:

  • To stay competitive in this digital world we’re living in, a company must utilize its data, its asset.
  • Organizations that have high data literacy are well ahead in leveraging their data compared to other organizations.
  • “One of the greatest ways an individual can start to get better with data and analytics is to become curious – start asking the question, why?”
  • Own the chart data in the dashboard that is put in front of you. Figure out why the data appears and where comes from.
  • Experiment with questions of the data to figure out questions that work and do not work.
  • When finding questions about the data that work or do not work, ask why that is the case.
  • Start reading books about data. To start, peruse Factfulness by Hans Rosling.

 

SOURCE: https://www.dataversity.net/the-importance-of-data-literacy/

With respect.

 

 

 

Valuable lessons: Your Data Is Worth More Than You Think by MIT Sloan Management Review.

Over the last just two years, I started getting more passionate about data. When I started watching a video from the World Economic Form regarding Fourth industrial revolution, I started noticing how digital transformation is skyrocketing. I deliberately started my keen interest on the Internet of Things, Artificial Intelligence and 3D printing too. To be honest in 3D printing, I don’t know how data works. To learn a fair view of those topics, I seen the term “Data”. Data matters here to learn. That is what makes to me to pursue the Data Scientist course.

So this is an article about data gives you views about data valuation with three basic reasons. I pasted the source link down below. I sincerely encourage you all to visit further.

About the Authors

With over 20 years in advanced analytical applications and architecture, John Akred is a recognized expert in the areas of applied business analytics, machine learning, predictive analytics, and operational data mining. He has successfully delivered applications using a wide range of architectural approaches — including stream processing, in-database analytics, complex event processing, real-time optimization, event-driven architectures, and more — at scale. He tweets @BigDataAnalysis. With a background in machine learning, Anjali Samani is adept at managing and delivering commercial data science projects across a range of industries. She has nearly a decade of experience as a quantitative analyst in investment management, focusing on financial modeling and risk analysis, and is passionate about enabling organizations to identify innovative solutions through effective use of data. Anjali tweets @AnjaliSamani.

Even when company leaders recognize that their data has value, they have difficulty measuring that value accurately — and it can cost them.

Data has become a key input for driving growth, enabling businesses to differentiate themselves and maintain a competitive edge. Given the growing importance of data to companies, should managers measure its value? Is it even possible for a company to effectively measure the value of its data? An increasing number of institutions, academics, and business leaders have begun tackling these questions, leaving managers with many alternatives for assessing the value of data. None are yet generally accepted, nor completely satisfactory, but they can help organizations realize more value from their data.

Why Is Data Valuation Important?

There are three basic reasons organizations want a good way to understand the value of their data. A good sense of value can help guide good decisions around direct monetization, internal investments, and mergers and acquisitions.

Direct Data Monetization

Many organizations are keen to monetize data directly by selling it to third parties or marketing data products. Inability to understand data’s value can result in mispriced products. Understanding the impact of exposing data to third parties on the value of a company’s data for indirect monetization can help guide the decision on whether to pursue explicit monetization. Today, despite an increasing recognition of potential benefit, most organizations are very conservative about what data they expose outside the enterprise. Good valuation approaches could help leaders understand if selling their data would really affect their competitive position or ability to realize their own benefit from it.

Internal Investment

Understanding the value of both current and potential data can help prioritize and direct your investments in data and systems. In our experience, most organizations struggle to articulate the relationship between their IT investments and business value generally. For data systems, the problem is particularly acute. Surveys report that only about 30% to 50% of data warehousing projects are successful at delivering value. Understanding how data drives business value can help you understand where you should be minimizing costs, and where you should be investing to realize potential ROI.

An ability to articulate data’s contribution to an organization’s overall value can transform the relationship between technology and business management. Chief experience officers (CXOs) charged with managing data report that their ability to articulate business value from data investments with rigor supported by the CFO results in more resources available to drive more positive outcomes for their organizations.

Mergers & Acquisitions

Inaccurate valuing of data assets can be costly to shareholders during mergers and acquisitions (M&A). Steve Todd, an EMC fellow, argues that data valuations can be used both to negotiate better terms for initial public offerings, M&As, and bankruptcy, and to improve transparency and communication with shareholders. Did Microsoft Corp.’s purchase price of LinkedIn Corp. include the value of LinkedIn’s data about professionals and companies? Did they survey potential uses of data in the combined company? The assumption that data’s value is captured only by sales and revenue figures may understate the overall value of a transaction to the benefit of the buyer — and to the detriment of the seller.

Current generally accepted accounting practices (GAAP) do not permit data to be capitalized on the balance sheet. This leads to considerable disparity between book value and market value of these companies, and a possible mispricing of valuation premiums. While internationally agreed-upon standards may emerge in the next five years, the Association of Chartered Certified Accountants (ACCA), the global professional accounting organization, is encouraging accounting companies to come forward with approaches. Wilson and Stenson provide an excellent review of accounting approaches that recognize and value intangible assets in general, and information assets in particular.

Existing Approaches Are Useful, But Limited

Methods for valuing data are varied. Most descend from existing asset valuation or information theory. Some attempt to attribute the value of business outcomes directly to data-driven capabilities. Like statistical models, all have limitations, but some are useful.

Dell EMC Global Services Chief Technology Officer Schmarzo developed the so-called “prudent value” approach, which values data sets based on the extent to which they could be used to advance key business initiatives that support an organization’s overall business strategy. This approach has two main advantages:

  • It provides ballpark valuation (or a range of values) for the data set derived from the financial value of the business initiative.
  • More important, it frames the data valuation process around the business decisions that need to be made to drive the targeted business initiative. It quantifies the ways in which different data sets might be utilized and the impact this could have on the success of the targeted business initiative.

Mapping data to valuable outcomes can fulfill many purposes of data valuation. It supports rigorous ROI arguments based on concrete business outcomes for IT investment decisions. It can also guide pricing direct monetization efforts by relating the business value of the decisions third parties use with respect to data to guide the price they might pay for access.

Some of the most comprehensive work on the subject of data valuation comes from Gartner Inc.’s Douglas Laney. Laney, vice president and distinguished analyst, Chief Data Officer Research, proposes “infonomics” as an economic discipline, arguing that information should be treated as an actual corporate asset — measured, managed, and deployed as if it were a traditional asset. Laney describes six different information valuation methods, three foundational and three financial.

The foundational methods are primarily aimed at businesses that wish to prioritize or create an aggregate of data quality characteristics to get a sense of what its relative or intrinsic value is. These methods force businesses to take stock of their data, how they are leveraging it (or not!), and ultimately articulate its value and evaluate what is and isn’t useful. Laney’s financial measures draw on methods to value intangible assets.

The biggest limitation of Laney’s approach is that it does not tie the value of information to its role in supporting business decisions. His approach is more likely to be useful for valuing data in M&A transactions.

Where to Start

While there is still room for significant improvement in how to value data, current methods can still be useful to enterprises. Organizations should begin efforts to:

  • Create management consensus on how to build business cases for IT investments in data, infrastructure, and capabilities.
  • Use data valuation to prioritize data investments.
  • Begin cataloging and estimating value from existing and potential data-driven capabilities to inform valuation on the public markets or in M&A transactions.

Organizations that become more capable of getting value from data will certainly realize benefits and competitive advantage. Developing the ability to understand data’s value, and contribution to outcomes, is an important part of delivering that value.

 

SOURCE: https://sloanreview.mit.edu/article/your-data-is-worth-more-than-you-think/

 

With respect.

 

 

Valauble lessons: The value of data by World Economic Forum.

Data is dominating. We started generating much more data than ever before. There is a reason for sharing this article. Although, there are several articles dealing with data. But this is also the most important one to look at it. We knew very well that we are living in a data ecosystem. There is no doubt about it.

What is happening with data?

So, this article says a fair view about data. I personally think this is the right time that we must give more attention to the value of data and our data too.

I’m gonna paste source link down below. I sincerely encourage you all to visit further.

The value of data:

Recently, Equifax, a US based consumer credit reporting agency that collects and aggregates information on over 800 million individual consumers and more than 88 million businesses worldwide, suffered a data breach of 143 million users. As a result, they’re facing a class action lawsuit of up to US$ 70 billion.

In 2015, an insurance company compensated its 75,000 users with $100 per person for breach of their personal data. These are just two of the several cases of data breach, which over the past few years have become a frequent occurrence. Alongside these developments, on 17 August, the Supreme Court of India passed a landmark judgment reinforcing the citizen’s right to privacy as a ‘fundamental right’. These incidents highlight the emerging issues surrounding data – its privacy, security and sovereignty. To discuss and resolve these issues, it is imperative to be cognizant about the value of data. In this age of hyper connected consumers, data is definitely the new age ‘oil’.

The question that this data revolution then presents is – who will be the winners and losers as the age of open data takes off? To arrive at a credible and satisfactory answer, it is important to analyse the value of data from different perspectives, that of an individual, corporations and government.

The individuals, who generate the bulk of the data, and are its rightful owners, end up sharing it, sometimes with explicit consent and many times with implied, but uninformed consent. Individuals trade their private data in the digital economy for more tailored choices – goods and services, free applications and software, but don’t reap any monetary benefits from this exercise. The recent “Right to Privacy” judgement in India gives citizens and consumers in India a constitutionally guaranteed avenue to undertake measures for protection from data misuse, unauthorised collection and removes omnibus permissions making irresponsible reckless data sharing difficult.

Corporations have been the greatest beneficiaries from this data revolution. In 2006, oil and energy companies dominated the list of top six most valuable firms in the world, but in 2016, the list is dominated by data firms like Alphabet, Apple, Facebook, Amazon and Microsoft. Platform companies and data-aggregators capitalize on individual data by selling to advertisement networks and marketers looking to target specific segments, influence buyer behaviour and make dynamic pricing decisions.

Governments are increasingly becoming data savvy and leveraging open data for improving quality of life of its citizens by better design and targeting of welfare schemes, data driven policies, and improving participative governance.

The world produces 2.5 quintillion bytes a day, and 90% of all data has been produced in just the last two years. To assess the value of data for stakeholders, it is important to differentiate between data, content and information. Data is simple, raw and unorganized facts and consists of basic subscriber information (BSI), transactional data and content data. Transactional data is information related to communication such as IP addresses, device information used by subscribers to communicate and content data is the substance, purport or meaning of a communication. BSI and transaction data are together known as non-content data and were traditionally lower in the value hierarchy as compared to content data, but the same has changed in recent times and non-content data has been seen to provide critical insights. When this data is organized, processed and given a context, it can be termed as information. It is this information that is leveraged by corporations and is critical in decision making.

Data can also be segregated on a degree of how open or private it is. The degree of openness depends on local and societal norms. Public data, like any other public good is characterized by its non rivalrous and non excludable nature. In India, voter data is public data where their name, age, gender, address of all eligible voters is available online. Private data is such information that can only be accessed by people who have a legitimate reason to access it.

A person’s income is private data and must be protected from unauthorized access so as to prevent its misuse. Finally, confidential data is data that is highly sensitive and fairly personal, such as a person’s voting preferences. Confidential data is usually independent and inaccessible by the government (with some exceptions) and corporations with the individual exercising full ownership.

There is no standard practice or formula set in place to assess the value of data, but many more nations are becoming conscious of the enormous value data economy is creating. According to the European Commission, by 2020 the value of personalized data will be 1 trillion euros, almost 8% of the EU’s GDP. As this trend grows, there will be increasingly growing conflict between the value of data and individual privacy and consent.

The fundamental issue will become “Who owns the data and has intellectual property rights on it”? The global data economy is pegged at $3 trillion and consumers also need to reap the benefits of their self generated data. Data does have value in understanding, predicting and influencing individual behaviour and decisions, but it is exactly this power that makes it dangerous. As the world moves towards a universal online presence and open data systems, it is important to keep discussing the issues surrounding open dataand work towards resolving them, as opposed to viewing and evaluating data through the sole economic lens of a commodity.

Written by

Vasudha Thirani, Policy Associate, #DigitalIndia Foundation

Arvind Gupta, Chief Executive Officer, myGov, Government of India

The views expressed in this article are those of the author alone and not the World Economic Forum.

 

SOURCE: https://www.weforum.org/agenda/2017/09/the-value-of-data/

 

With respect.

How to Find More Time to Read

About The Author:

Kristina Adams is an author of fiction and nonfiction, writing and productivity blogger, and occasional poet. She has a BA in Creative Writing from the University of Derby and an MA in Creative Writing from Nottingham Trent University. She can be found under a pile of books with a vanilla latte.

Pretty much all of the most successful people in the world are voracious readers: Oprah Winfrey, Warren Buffet, Elon Musk, Bill Gates…

And if it’s good enough for them, it’s good enough for me.

Not to mention reading makes you more empathic, a better writer, and could even stave off dementia. Yep, I’ll take a book over an episode of Eastenders any day.

But, when you’re short on time, how do you find more time to read?

First of all, take some time and ask yourself how much time you spend on useless activities. You could easily sacrifice that daily episode of Eastenders for half an hour with a book. You’ll get more out of it and the books will be less likely to regurgitate storylines.

If you want to do something badly enough, you’ll find the time. Ereaders and mobile apps make it easier than ever find time to read wherever you are and whatever you’re doing. Let’s look at a few times and places where you can squeeze in a few extra pages. Because, while it may not feel worth it to read a few pages here or there, those pages add up fast.

Toilet trips

We’ve all got to do our business. Sometimes, we have to sit for a bit.

Most of us use this time to read random posts on our phones.

But what if you used that time to read instead?

If you read at one minute a page, and you’re on the loo for just ten minutes, that’s 10 pages.

Within a week, just from toilet trips, you’ll have read 100 pages.

Public transport

I hate public transport. Everyone cramped in together like sardines, suffocating on weed and fag fumes…

*Shudder*

I make it more bearable by reading. A lot.

Most of us spend at least fifteen minutes on public transport travelling to our destinations.

If you read a page a minute, you could read a 300 page book in 20 days.

20 days is roughly a working month, so imagine how much more you could read if you adopted these other habits too…

Queues

Despite popular opinion, we Brits don’t love queues. We complain about them a lot.

What we do love is manners. And respecting that someone arrived somewhere before you — and therefore waiting behind them — is a sign of good manners.

However, it’s amazing how much time you can lose to queuing. My mum and I once spent AN HOUR queueing for a carvery. I could’ve cooked a roast dinner from scratch faster.

Anyway.

Instead of complaining, use queues as an excuse to read a few more pages.

Waiting for…something

Waiting for family to be ready to go out.

Waiting to meet your friend for coffee.

Waiting for a film to start at the cinema.

Waiting for the car to defrost on a cold winter’s morning.

Almost any time you spend waiting for someone or something can be spent reading.

There’s always more time in the day

Like I said at the start, if you want to do something badly enough, you’ll find the time.

If you find it way too easy to put down the book you’re reading at the moment, maybe it’s not the book for you. Perhaps you should focus on building your reading habit before committing to such a yawn-inducing read.

Happy reading!

This was originally posted on The Writing Cooperative as ‘How to Squeeze More Reading into Your Day‘.

 

SOURCE: https://www.writerscookbook.com/find-time-read/

 

With respect.