Data quality is at the center of successful digital transformation, especially when your intention is to become an analytics-led or data-led company. As companies started embarking upon their digital transformation journeys, they quickly come to recognize the critical role of data.

Data is increasingly seen as the new “oil” powering digital transformation, enabling real-time, learning-based decision-making across all business operations, including product development, manufacturing, supply chain, and customer experience.

Data is where important and actionable business insights are derived. Yet, many enterprises and decision makers fail to understand what constitutes quality data and how it can be obtained, generated, collected, and utilized

“If you want to be successful in your Digital Transformation Imitative, Clean up your Data First”

The need for clean data is increasingly important as from 25th May 2018;
Most of companies are facing a long list of changes to comply with the GDPR but found that just 25% of existing customer data meets the requirements specified.

Quality Data enables organizations to predict trends, from consumer spending patterns to macroeconomic trends, enabling organizations to pool their resources and put themselves in the best position to be the first movers in emerging and future markets and Business intelligence is only as good as the quality of the data used to generate them. It is not just data, but quality data that fuels digital transformation.

However, what quality data looks like is not often clear to organizations. This affects the insights they generate and, thus, they fail to maximize the benefits they get from digital transformation.

Digital transformation primarily helps your company moving forward. It won’t immediately undo the years of issues created by data silos. However, you can get a significant amount of assistance from new solutions so you can streamline the process of fixing bad / poor data.

Data Quality is not a one-time project but a continuous process and requires the entire organization to be data-driven and data-focused. With appropriate focus from the top, Data Quality Management can reap rich dividends to organizations. It is a strategic approach enabling businesses to offer the best customer experience across all channels, by allowing for a unified view of all customer touch points.

Our Self-Service Data Quality will empower business users and data analysts to easily identify, fix and monitor the quality of data within and across all of their Applications, cloud or on-premise; thereby realizing faster and better business Outcomes.

This helps ensure that data is in the right shape to drive such business outcomes as deeper customer engagement, improved cross- and up-sell activities, better customer segmentation, increased marketing effectiveness and sales team productivity’s.

Reports are an important piece of any organization without insight information from reports, you would have no particular idea about how your business is performing financially, operationally, or something else.

Get instant reports on your business metrics and share insights with key people.

contact us — info@starcominfotech.com or visit our website www.starcominfotech.com/starbi.aspx for a free demo …!

Financial, operational, social and legal issues associated with poor or inappropriate decision making are extensively documented. However many organizations fail to manage their data quality issues effectively; or even at all.

Data quality management is costly, particularly when much of the effort is directed to non-critical data.

This thesis reports on research that developed a method to better target data quality effort and built a software artifact to explore the validity of the method. The method is to identify, rank and sort data using a mix of technical, user and business-based ranking points to reflect the usage and importance value for each data element.

The software artifact and method were tested in an experimental setting where different levels of random quality errors were introduced into a database and the impact of the errors assessed.

The relative merits of quality assurance using ranked data elements rather than outranked elements have been demonstrated.

The research was based on an extensive review of academic literature, commercial literature,and current commercial data quality products and services.

The thesis demonstrates the validity of a ranking approach to data quality. The method provides a means for organizations to improve their data quality assurance and thereby to improve their decision making confidence.

Get full Researched Report from: anberra.edu

The chart displayed above, from iot-analytics.com gives a nice comparison of some of the predictions from major IoT players like Cisco and Ericsson as well as IT research companies like Gartner and IDC have made recently. The range for 2020 is between 18 Billion and 50 Billion.

The first thing we notice in the chart is — they don’t all start in the same place! The initiation point ranges from 6 B to 14 B for 2014. That’s like having 10 stock analysts predict the future price of a stock in 5 years and all 10 have a different price on their Bloomberg terminal. Certainly a cause for worry. The second key point is that the rate of growth varies tremendously — from 14% to 23%. If this were a discounted cash flow model, and these ranges were being used to predict sales growth, the model wouldn’t have much validity would it?

So why don’t we, for the fun of it, try to do the math on this one? Let’s start by getting one thing straight — we will try to calculate the maximum number of connected devices by 2020. Not the mean or median or most likely — the maximum. This will make our choice of numbers way easier — we will choose the highest plausible number for each part of our calculation. Ok let’s get started.

Part I — The Humans and their Toys

There are currently 7.4 Billion people on Earth. There are 3.36 Billion people connected to the Internet In addition, there are around 2 Billion smartphones in the wild — give or take a few million. So -using the “maximum” adage we discussed earlier — lets assume the following:

1) By 2020, each person who currently owns a Smartphone will also own a laptop or some other kind of personal computer, including tablets. (This is NOT true, especially in Sub-Saharan Africa and Latin America where smart phones tend to be the only device people own, but its safe to say this would represent a reasonable Maximum)

2) The whole population of the Earth will have access to the internet by 2020. Again — who the hell knows — but its a good maximum. The world population will be around 7.7 Billion at that time — at least that is the highest number I could fine from a reputable looking source.

And now for the real wild assumptions. Lets say that the ratio of A) peeps who own a Smartphone to B) peeps who have internet will stay the same. Now that requires an intellectual leap of faith. We know internet access will not go down, but Smartphone access might hit a peak at some point before 2020. Here we are assuming it doesn’t. More people get internet, and thus more people get smart phones. Now — when we combine B) with 1) and 2) we are saying that (2/3.36)*7.7 = 4.58 B people will have a smartphone and a personal computer by 2020. So this brings us to 9.16 Billion connected devices that people use to access the internet by 2020.

Part II — The Industrial IoT

But what about the Industrial Internet of Things? Arduino, Raspberry Pi, sensors made by Ericsson, routers made by Cisco, drones, cars and planes? Well we can’t calculate that one based on the population of earth. But what about silicon chip manufacturing? Lets make some more assumptions:

3) This one is massive. Let’s say 35% of all silicon chip shipments in 2020 will go into some kind of IoT device (not including those used by people directly). The raspberry pi 2 has a 900 MHz quad-core ARM Cortex A7 processor. Now suspend disbelief and imagine that every single factor floor in the world that makes silicon chips and processors will be rolling out this processor’s descendants in 2020. According to SEMI, in Q3 2015 there were 2,591 Millions of Square Inches (MSI) of silicon materials shipped. In June 2015, Freescale semiconductors revealed the i.MX 6Dual SCM processor -which measures in at 17mm X 14mm X height. That is .66929 Inches * .551 Inches = .3688 square inches. You can make 7.025 Billion (2.591/.3688) of these processors in one quarter in 2016.

4) Great, so let’s say this becomes the norm in 2020. If these IoT chips represented 35% of all the silicon chips produced in the world, that would be .35 * 7.025 Billion in one quarter and .35 * 28.1 Billion = 9.835 Billion in one year.

5) For the sake of keeping this article at less than a million pages, let’s say that the number in 4) will be the number of Industrial IoT chips we have in the wild in 2020.

Great. We are done! Adding the results from part I and II we get: 9.16 Billion + 9.835 Billion = 18.995 Billion connected devices by 2020

Hey that’s just barely above the lowest number on the chart! Either our calculations are too conservative or everyone else is too optimistic.

Of course you could make the argument that using 35% in assumption 3 is a bit arbitrary. Granted. But given the fact that WSTS said smartphones and computers alone made up for 65% of all semiconductors in 2014 (blog.semiconductors.org) it doesn’t seem like such a crazy assumption. Going with the mantra of reaching the absolute maximum number given somewhat reasonable assumptions, we could say 50% (gasp!) of all semiconductor production will go towards industrial IoT in 2020 which would lead to 14.05 + 9.16 = 23.21 Billion devices. That’s still 5 billion less than the second lowest estimate (from IT research group IDC) on the chart.

Conclusion: If someone tells you there will be 50 Billion connected devices by 2020, tell them to read this article.

I recently attended a very popular IoT conference in Silicon Valley. During a presentation, the keynote speaker asked the audience, “Who here is building a connected product?” About two-thirds of the audience raised their hand. Then he asked, “Who is making money with IoT today?” No hands went up this time.

This little engagement trick reinforced the fact that many companies are jumping into the opportunity of building IoT products without a clear monetization strategy or put more simply, a strategy for how to make money from your IoT product

Here’s Top IoT Business Models in use these days.

#Commercial Based -Model

The Commercial-based model is an example of an innovative approach enabled by IoT products. The idea is for customers to pay for the outcome (or benefit) the product provides, as opposed to the product itself.

#Asset-Sharing Model

A big concern when buying expensive equipment is whether the customer will be able to utilize the equipment to its maximum capacity. This is where the idea of sharing assets comes into play. We are starting to see this model already with Automotive companies.

Think about it like this: why do I need to pay the full price for a car if it’s going to be parked outside my house 90% of the time. Could I just pay the amount of car I use?

IoT has the potential to solve this problem, and we are already starting to see solutions with self-driving cars, virtual power plants, shared drones, and more.

Recommended for you: Monetization Strategies for Connected Products

This IoT business model revolves around selling your extra capacity back into the market. The goal is to maximize the utilization of your product across multiple customers. That way, each customer pays a reduced price and you are able to get faster market penetration, compared to when a single customer has to pay for your complete product.

#IoT Product as a Proxy to Sell another Product

Your IoT product can be a conduit for selling other products. during this model, you may sell the IoT product at a value or maybe at a loss since the goal is to get the product in the customer’s hands so you can start selling your other products. This approach reminds me of the early strategy from Ford, where the plan was not to make money on the cars themselves, but on the parts and service.

Amazon uses this model with their Amazon Dash Buttons. These “connected buttons” return pre-configured to order a particular product, say detergent or toilet tissue. you press the button, it re-orders that item from Amazon and it arrives at your door within a few days.

Amazon’s goal is to provide “contextual shopping”, that means the flexibility to reorder a product right once you want it. By introducing this clever connected product, Amazon is reducing the barriers for you to re-order any product you would like. In this case, the Amazon Dash Button isn’t a revenue maker in itself, it’s simply a vehicle to sell different merchandise in Amazon’s catalog.

#IoT Products as a Vehicle to Monetize Data

The value of IoT is within the insights you’ll be able to derive from the info you collect, data has become the world’s most precious resource. The question is, who benefits from the data and insights? Think about corporations like LinkedIn or Facebook. They collect a huge amount of data from all of us (often for free) and though they provide us (the user) with the price for providing that data with value for providing that data, the real value is provided to advertisers and other third-party companies that use that data to promote their products and services.

In this case, LinkedIn or Facebook are tools to collect data to offer to advertisers.

The same model works in IoT. you’ll be able to build your product to provide price to the end user, and additionally to gather valuable data you’ll be able to then sell to a 3rd party. during this approach, you’ll be able to provide your IoT device at no cost to eliminate the friction with the end user. The goal is to deploy as several devices as the potential to gather data.

#The Bottom Line

As a Product Manager, it’s important to understand how your product adds value to your user and to your company. So it is very important to have a clear strategy for how to monetize your product. The good news is that IoT products provide many new and innovative business models for monetization of your product.

This article originally appeared on iotforall Blog

Workspace analytics and IT asset optimization can harmonize your resource stack and identify waste.

We are in the midst of the workspace revolution — and it’s more than just immersing ourselves in industry buzzwords such as “co-working”. This transformation is full circle — and we are starting to see typical transaction relationships humanize between landlords and tenants who are demanding a fully serviced and tech style offering. This industry has never been more energized or exciting to be a part of!

The evolution and understanding around the importance of the right technology in the right workspace will be continued in 2018!

End users are people too! This relates to ‘what does a successful user look like and how can we replicate that success at scale?’ We need to learn how to segment and personalize their IT experience for better performance in the organization.

Workspace analytics can help organizations determine how end users are using their applications. Everyone uses applications differently and don’t forget about month end, quarter end and year end task that will likely demand more resources from the hosts.

With workspace analytics its very easy to collect ‘Data’ about the end user work patterns & styles, that allows organizations to make the best decisions, based on evidence, for delivering highly available workspaces, improving the end user experience and efficiency of the workspace they operate in.

Workspace anlaytics can put answers to questions such as: “What is our user experience? “ or “who is having slow logon times?” or “what is impacting user experience right now?” at your fingertips in no time.

Then why not use workspace analytics to identify the correlation between very high Workspace % health & efficiency scores to departmental / regional revenue growth or loss patterns?

The automation of Persona’s using Lakeside systrack Analytics, enables organizations to gain greater controls of the end user workspace, ensuring every user always gets the workspace they need, when they need it, with a consistent qos delivered no matter what platform, device, application they use, across any region or location they operate in.

Lakeside Software also provides essential IT telemetry for Windows 10 with their systrack end-user analytics platform. Systrack helps customers reduce helpdesk costs and improve risk management by providing an ‘inside out’ view of desktop performance and user interactions.”

1) Credit card fraud:

-They will create another credit card account in your name.
-They will use the card and will not pay the bills and this account will show in your credit report.
-They may change the mailing address of your credit card and for that reason you will not receive any bills at your home and by the time you realize you will have to pay a good amount for not paying bills.

2) Phone or utilities fraud:

-They may create a new phone or wireless account in your name and just increase the amount of charges which you will have to pay.
-They may use your name to use utility services like cable TV, electricity and heating etc.

3) Bank/finance fraud:

-They may create forge cheque book to get the facility of a cheque
-They may open new bank account in your name and write bad cheques
-They may create duplicate ATM card and can withdraw amount from your account using that card.
- They may take loans from different banks using your name.

4) Government documents fraud:

-They may create new office ID card and driving license with their picture instead of yours.
-They may use your social identity number to get the government facilities.
-They may file a fake tax return using your financial information.

5) Other fraud:

• They may use your social security number to get a job.
  -They may use your identity to get the facility of medical treatment.
  -They may give your details to the police and when the person will not visit to the court then an arrest warrant will be issued against your name

Read More: — Trusted Digital Identities

As of 2017, 7.5 billion people use the Internet — thats nearly 52% of the world’s population. As many aspects of our lives become increasingly digital, there is a need and expectation for our finance-related processes to be digital too. A recent survey conducted by the Harvard Business Review shows that 73% of all consumers use multiple channels while shopping and that multi-channel consumers spend more money than their single-channel peers.

Digital consumers need to interact with banks and financial services online — with mobility and security. Fintech disruptors and established organizations who’ve found ways to leverage their legacy systems are taking the lion’s share of customers — especially the tech savvy Generation X and Y target markets.

There is an ART to overcoming perceived and real challenges to transformation, and OpenLegacy offers banks and financial institutions the help and resources needed to quickly and successfully meet customers’ digital expectations. In this blueprint learn how to implement the ART of the API in order to achieve:

• low Cost
• Speedy Implementation
• Software quality and security
• Fully functional digital services in minutes instead of months
• Seamless customer experience
• Drive new revenue
• Reduce customer churn

Read full Story: THE FUTURE OF BANKING & FINANCIAL SERVICES DEPENDS ON APIs

Not even a small and successful business.

So what’s the secret to keeping your people efficient and productive, while recruiting the best talent and retaining them without falling victim to a rapid employee turnover rate?

One answer: employee motivation

The bad news is… there is no exact formula you can follow in motivating employees so they stick with you through thick and thin. Every company is different. And so is the way each one is run. The company culture in one enterprise may be different from your own, so it’s not just a matter of following random generic guidelines for motivating employees because every single one of your people needs a specific something that makes them tick.

Some employees may be motivated by money. Others require appreciation and recognition for their work. Still others are moved by company perks like vacation days and medical insurance.

Which brings us to the good news… motivating employees is as simple as finding out exactly what your people want, and finding ways and means to give it to them… either outright, as incentives, or as targets they can reach.

Here are some techniques you can use to become more attuned to your employees’ needs and to make you more aware of how you can motivate your number one company resource — the people who work for you:

Be a one-on-one manager — as stated earlier, no two companies are alike. Ergo, no two workers are alike, either. Take time to get to know your people. Sit down with them, ask them how they are, inquire about their families, hobbies, pets, pet peeves. In fact, the very act of spending some time with them, no matter how brief, will make them feel they are important and acknowledged, and that goes a long way toward motivating employees into spending long hours on overtime or taking on extra work without extra compensation. More importantly, you become better aware of their individual desires, rather than what you perceived to be a collective employee demand. Just as your company strives to treat each customer uniquely based on their individual needs, you can tailor perks and incentives based on your own people’s needs. Some creative examples include giving employees the opportunity to audition company furniture like desks and chairs and allow them their say on the most comfortable ones that suit them, ordering sugar-free, kosher or vegan meals for company functions, or even something as simple as approving flexible hours for some of your people.

All for one, one for all — wouldn’t it be great if everyone in your company were like one happy family? Motivating employees this way can involve encouraging coffee breaks where everyone shares food, drink and non-business talk for at least 15 minutes everyday. Invite all your people, not just department heads or your creative director, to brainstorm ideas for the company. Get everyone involved to make them feel their opinions count and they’re a part of the company’s success.

Put a square peg in a square hole — in other words, allow your people to shine in the roles that suit them best. Do you have someone in the technical department who you feel would perform better in customer service? Is someone in the mail room raring to give marketing a try? Discuss these possibilities with your employees instead of shuffling them off to HR to work out the transfers. Motivating employees may sometimes mean recruiting in-house to fill a talent void, or having your people test drive new responsibilities and allow heretofore unexploited abilities to be recognized. And if the move to the new department or position is highly successful, then you have a satisfied employee who’ll be more than happy to continue to shine.

Have some friendly competition — know what builds company morale all around? Competition. No, not competition for jobs, or promotions, or for who get to hold the boss’ ear the longest. Motivating employees can sometimes take you out of the box…the cubicle box, that is. Stage some sort of competitive event, like an annual basketball or holiday decorating contest per department. Or if you want to keep it work-related, create competition based on the kind of business you run. If you’re in the food industry, for example, hold a best recipe contest, and make the winning entry part of your company’s product offerings.

Have fun — incorporating fun into your daily work day will help your people get into the groove without turning into grumpy, uncooperative zombies by mid-morning. Motivating employees can be as simple as sending a daily joke or anecdote through email or voicemail, charging $1 to people who come in late to meetings and divvying up the reward among those who come on time, putting up a bulletin board for staff to post their creative work, funny messages or quips…

Are you ready to experience new levels of productivity through workspace analytics?

Workspace analytics is a framework for making high-level IT decisions that provides meaningful insights into business productivity by analyzing end users, the business processes that encompass their jobs, and the technologies they use to get work done. By considering IT operations as a whole component of a business engine rather than a series of isolated gears, decision makers can strategically provision time and resources to address the evolving technological needs of the modern workforce.

How Should Big Data Be Used in the Workplace?

The concept of using Big Data and HR Analytics in the workplace has become a debatable issue but the term Big Data and all the commotion that surrounds it ends up obscuring a fundamental point in managing organizations and its employees regardless of their size. We passed definitely to an era of huge amounts of data, where the challenge of all employees will find new ways to analyze this information overload, get practical insights, implement changes and analyze new data in order to compare predictions and actual results. The test days and no less than a central point of the day-to-day operations of an organization it were entered in a continuous and uninterrupted period change.

This new world requires experimentation. Organizations thriving in the coming years will be those that can adapt to the environment.

Gold in Terabytes: How is big data really changing or affecting the workplace?

There are extraordinary gains to be made, taking advantage of the opportunities that the new era immersed in data offers. The wealth of information offers tantalizing prospects, as experienced management teams and their advisors direct companies willing to work in a vicious cycle of continuous improvement, identifying attractive growth opportunities, providing improvements in profit margins by eliminating unnecessary expenses and so general, promoting improvements in the value added of the company.

We are directing far beyond the mere analysis of SKU (Stock Keeping Unit) and the development of models optimized price allocation. By understanding high-quality data sources both inside and outside organizations, inefficient sectors can be attacked relentlessly and with the continuous flow of data that many organizations offer, small projects that produce results can be rapidly extended to enterprise-wide initiatives.

There will be victims Based on what is seen in the market, it is anticipated that small and medium sized companies able to adapt will find a more efficient business model, using the data as a multiplying force. Organizations that fail to adapt will find themselves in a position of increasing disadvantage as their competitors use deeper information to grow in the marketplace and identify new opportunities.

Blind adherence to information can also cause damage. Massive sets of data are, almost by definition, “noisy” and abstracting useful ideas from it must always take into account both the forces of the set and its limitations. Ironically, this increasingly analytical field requires, more than ever, a solid qualitative basis to ensure that quality checks are not overlooked.

Learn more about what workplace analytics can do for your business ?