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Citizen Data Scientists: Who Are They & What Makes Them Special?

Citizen Data Scientists: Who Are They & What Makes Them Special?

Companies across the globe are focusing their attention on data science to unlock the potentials of their data. But, what remains crucial is finding well trained data scientists for building such advanced systems.

Today, a lot many organizations are seeking citizen data scientists – though the notion isn’t something new, the practice is fairly picking up pace amongst the industries. Say thanks to a number of factors, including perpetual improvement in the quality of tools and difficulty in finding properly skilled data scientists!

Gartner, a top notch analyst firm has been promoting this virgin concept for the past few years. In 2014, the firm predicted that the total number of citizen data scientists would expand 5X faster than normal data scientists through 2017. Although we are not sure if the number forecasted panned out right but what we know is that the proliferating growth of citizen data scientists exceeded our expectations.

Recently, Gartner analyst Carlie Idoine explained a citizen data scientist is one who “creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.” They are also termed as “power users”, who’ve the ability to perform cutting edge analytical tasks that require added expertise. “They do not replace the experts, as they do not have the specific, advanced data science expertise to do so. But they certainly bring their OWN expertise and unique skills to the process,” she added.

Of late, citizen data scientists have become critical assets to an organization. They help businesses discover key big data insights and in the process are being asked to derive answers from data that’s not available from regular relational database. Obviously, data can’t be queried through SQL, either. As a result, citizen data scientists are found leveraging machine learning models that end up generating predictions from a large number of data types. No wonder, SQL always sounds effective, but Python statistical libraries and Jupyter notebooks helps you further.

 A majority of industries leverages SQL; it has been data’s lingua franca for years. The sheer knowledge of how to write a SQL query to unravel a quiver of answers out of relational databases still remains a crucial element of company’s data management system as a whole lot of business data of companies are stored in their relational databases. Nevertheless, advanced machine learning tools are widely gaining importance and acceptance.

A wide array of job titles regarding citizen data scientists exists in the real world, and some of them are mutation of business analyst job profile. Depending on an organization’s requirements, the need for experienced analysts and data scientists varies.

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DataRobot, a pioneering proprietary data science and machine learning automation platform developer is recently found helping citizen data scientists through the power of automation. “There’s a lot happening behind the scenes that folks don’t realize necessarily is happening,” Jen Underwood, a BI veteran and the recently hired DataRobot’s director of product marketing said. “When I was doing data science, I would run one algorithm at a time. ‘Ok let’s wait until it ends, see how it does, and try another, one at a time.’ [With DataRobot] a lot of the steps I was taking are now automated, in addition to running the algorithms concurrently and ranking them.”

To everyone’s knowledge, Big Data Analytics is progressing, capabilities that were once restricted within certain domains of professionals are now being accessible by a wider pool of interested parties. So, if you are interested in this new blooming field of opportunities, do take a look at our business analyst training courses in Gurgaon. They would surely help you in charting down a successful analyst career.

 

The blog has been sourced fromdatanami.com/2018/08/13/empowering-citizen-data-science

 

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#TimeToReboot: 10 Random, Fun Facts You Must Know About IT Industry

#TimeToReboot: 10 Random, Fun Facts You Must Know About IT Industry

Indian IT sector is expected to grow at a modest rate this fiscal year, which started from April – companies are expanding their scopes and building new capabilities or enhancing the older ones. Demand for digital services is showing spiked up trends. The good news is that the digital component industry is flourishing, faster than expected. It’s forming a bigger part of tech-induced future, and we’re all excited!!

On that positive note, here we’ve culled down a few fun facts about IT industry that are bound to intrigue your data-hungry heart and mind… Hope you’ll enjoy the read as much as I did while scampering through research materials to compile this post!

Let’s get started…

Email is actually older than the World Wide Web.

Our very own, Hewlett Packard started in a garage… In fact, several other top notch US digital natives, including Microsoft, Google and Apple had such humble beginnings.

Bill Gates’ own house was designed using a MAC PC, yes you heard that right!

The very first computer mouse was carved out of wood. Invented by Dough Engelbart, first-ever mouse wasn’t made of any plastic or metal of any kind, but plain, rustic WOOD.

The QWERTY keyboard, which we use now, is simple, easy to use and effective. But, did you know: DVORAK keyboard was proven to be at least 20X faster?

The original name of Windows OS was Interface Manager.

Do you think 1GigaByte is enough? Well, the first 1 GB hard drive made news in 1980 with a price tag of $40.000 and gross weight of 550 pounds.

Very first PC was known as ‘Simon’ from Berkley Enterprise. It was worth $300, which was quite an ostentatious amount back in the 1950s, the year when this PC was launched.

In 1950’s computers were called ‘Electronic Brains’.

1 out of 8 marriages in the US happened between couples who’ve met online. Wicked?

 

Feeling excited to know all these stuffs… Now, on serious note, in the days to come, the Indian IT industry is all set to transform itself with high velocity tools and technology, and if you want to play a significant role in this digital transformation, arm yourself with decent data-friendly skill or tool.

The deal turns sweeter if you hail from computer science background or have a knack to play with numbers. If such is the case, we have high end business analyst training courses in Gurgaon to suit your purpose and career aspiration – drop by DexLab Analytics, being a top of the line analytics training institute, they bring to you a smart concoction of knowledge, aptitude and expertise in the form of student-friendly curriculum. For more details, visit their site today.

 

The blog has been sourced from:

qarea.com/blog/facts-from-the-it-industry

forbesindia.com/article/leaderboard/indian-it-services-sector-time-for-a-reboot/49671/1

 

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How To Incorporate Embedded Analytics In Your Products or Applications?

How To Incorporate Embedded Analytics In Your Products or Applications?

The adept R&D team shares a common responsibility – devising incredible products and solutions.  Right from VPs and directors of development to DevOps and system engineers – every professional is well aware about their customer expectations.

In today’s data-driven industry, customers desire to collect information regarding product use, numerous status updates, number of times they engaged with the product and so on. In short, they need access to data that not only help unravel crucial insights but also makes the product fetching.

Definitely, you can create your very own analytics solution, but what if it takes so much time that your competitors outgo you? So, what next?

Embedding analytics into your product or application can be your thing for the day, but how to do it effortlessly?

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Collect Data from Various Sources

We are surrounded by IoT (Internet of Things) and IIoT (Industrial Internet of Things) revolution, where each connected device and sensor accumulates data and this collection and analysis of data is significant to customers. Teams need to sit together and discuss out options for creating an analytics overlay for the product, which will trigger a million questions – how can we get through it? Will our solution scale the growth of number of users? How can we go on improving our products? How do we keep up with all the developments happening in analytics?

Things to Consider While Embedding Analytics

“Start by looking for specific analytic applications that complement your ERP and BI platform investments. In the long term, review vendor capability to support reusable analytics artifacts (i.e., services) in a service-oriented architecture environment,” – says Gartner.

To this, we’ve listed a few functionalities waiting for your attention:

Data Access – How simple do you want your platform to be so as to integrate your data well across all sources and types?

Visualization – Does the platform you chose comprise widgets you need? If not, can you develop them using customization options?

Modeling – How much easier will it be to code for data preparation for user consumption?

Embeddability (iFrame, JS libraries, JavaScript) – Dashboards should be built in a way to suit your customer’s requirements either in mobiles or in web-based applications.

Extensibility (APIs, SDK, JavaScirpt) – No hard fact, for incorporating analytics workflow, solutions supporting API is the key. Otherwise, not getting extensibility will leave you tied to the same analytics platform and can cost you consulting fees and vendor-developed modifications.

Process integration – Generally, integration takes months – so find a vendor who is capable enough to integrate with your products in a week or two so that you remain focused on the benefits alone.

Security – Judge a vendor based on his security credentials – it’s one of the most crucial considerations to tick off your checklist.

As last thoughts, the consideration of these 7 functionalities is just the beginning of embedding analytics into your products or applications. To sail through, the most important thing to do is to choose a suitable vendor who will grow and start thinking of you as a partner and not just any customer. Let him offer you quick, easy and seamless integration, and you solely focus on your customer needs and preferences, and for this, they will LOVE YOU for sure!

If you are still confused about embedded analytics or related concept, let career-building business analyst training courses in Noida help you! For more information on business analyst training delhi, drop by DexLab Analytics.

 

This blog has been sourced from – https://www.sisense.com/blog/going-embedded-pillar-analytics-success

 

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5 Expected Changes You Are Going to Witness Once You Move to SaaS

Moving to the cloud takes time. One of our friends started with Salesforce in 2009, after 5 years they introduced G Suite (widely known as Google Apps during that time) and it’s now in 2017 that they have adopted a fully cloud-based electronic health record facility. It took 10 years for an organization to resort to a handful number of installed applications for smooth handling of specialized tasks.  

5 Expected Changes You Are Going to Witness Once You Move to SaaS

Nevertheless, their shift to Software-as-a-Service (SaaS) has had an impact on IT spending. Though the expenditure varies from company to company, every organization must have experienced these 5 changes highlighted below:

 

Let’s Take Your Data Dreams to the Next Level

Better networks

Unsurprisingly, people need and expect faster internet speed these days. Even small businesses have connections that deliver 250Mbps down and 75Mbps (or more) up. An interesting switch is being observed in infrastructure. Today, more or less any medium-organization boasts of 802.11n or 802.11ac WIFI networks, which was unimaginable even few years ago. Deploying wireless mesh devices has become the order of the day now.

Lesser computer upgrades

There was a time, when we used to think that we have to replace our computers every three or five years. In several cases, we had even planned to make a few upgrades to the hardware to keep them running (RAM and hard-drive replacement was a common thought).

But in reality, organizations seldom have to replace parts. In most offices, five year old desktops perform perfectly in delivering the right results. This means definitely days of upgrades are over, all that matters is a faster internet speed and robust app development.

 

More usage of “plug-in and use” systems

More and more companies are seeking so-called “sealed” systems. Though some big companies still go on deploying standardized drive images, but increasingly organizations are found picking off-the-shelf sealed devices, like all-in-one desktops and non-use-configurable laptops.

 

As organizations are moving towards SaaS, Chromebooks are becoming increasingly famous. In fact, more than 20% of the team mentioned in the beginning of the blog uses a Chromebook as their primary work device.

Longer life for devices

Devices, like desktops and laptops that have embraced SaaS seem to have a longer lifecycle. As SaaS mostly depends on browser and network performance, the need for replacing devices has decreased to a great extent. Systems work totally until the device fails to perform or no longer in a position to receive any updates. Also, with SaaS, crucial data don’t remain solely on the device, hence if a system fails, little seems to be lost.

Considerable attention to the peripherals

Peripherals are intimidating. A large number of conventional desktop units have a scanner, printer and copier devices that are supported by a locally installed Windows software or server. Organizations can easily find alternatives of these devices, but it will take some time and effort as well. Few applications and sectors still suffer from minor or significant glitches, but over time, we hope peripherals and accessories will start showing signs of improvements.

 

What changes have you noticed in cloud computing and storage? How do you think the landscape of IT has changed over the past decade?

 

 

To better understand the intricacies of cloud computing and data storage, opt for business analytics course in Delhi from DexLab Analytics. They offer excellent analyst courses in Delhi at really affordable prices. Check out the course itinerary today!

 

The article has been sourced from – https://www.techrepublic.com/article/5-changes-companies-will-see-after-moving-to-saas

 

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How to Develop a Data-Driven Culture among the Employees and Organization?

Data creation and consumption is exploding. So is the challenge of analyzing data and transforming it into actionable insights.

How to Develop a Data-Driven Culture among the Employees and Organization?

The expert consultants at IBM say – 90% of the data in the world has been created in the last couple of years at a rate of 2.5 quintillion bytes per day. Just imagine, when such gold mines of information go unused, what toll does it take on companies who harbors them? The loss is insurmountable, isn’t it? 

But the question that makes us brood is how do companies empower employees to use such vast pools of data to reveal hidden business insights?

To keep pace with an accelerating growth of data generation and robust competitive landscape, new age companies need to shift their focus to sound Business Intelligence solutions that helps in collecting and analyzing data to determine patterns and alert users, in case of anomalies in the nature of business. And the good news is that they are doing so.

Once companies start off with data handling and data mining, the issue of utilization needs to be addressed next – the trickiest problem with data utilization is the insights that take place within the departments –while creating data silos. Siloed data results in creating a lot of issues, but the larger one is that it creates only a partial view of whatever is happening within an organization and a bigger picture is not available.

As a result, a data-driven culture is to be adapted – but how?

 

Let’s Take Your Data Dreams to the Next Level

Right from the top-level

The true DNA of any organization lies within its top-level management team, including the founders and managing directors – and that’s where the foundation stone of data-driven culture should be implanted. Implementing something new and offbeat is intimidating, but when the company leaders promote it, the idea gains familiarity and merges with other data-driven decisions.

Empowerment

Employees need to feel empowered – then only they can independently mine data and share crucial findings with colleagues and seniors without asking for help from the IT guys. A common misconception that exists around is that data analytics is a cumbersome task which requires heavy involvement from IT- but in reality, things are changing – BI tools are being revamped to make users more independent and self-sufficient to take better business decisions.

Time and again, it’s important for the executive management to show some token of appreciation to employees for their hard work. It is in these subtle ways the data-driven culture gets promoted across company walls.

 

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Sharing is caring

Now, the data siloes come into the picture. Once employees are comfortable with using data and bearing the fruits of success – insights need to be shared across the business fronts to draw a much larger picture.  Not only it promotes cross-team and departmental collaboration, but also brings in newer data into the limelight that wouldn’t have been possible before. Hence, sharing of insights is crucial for business success.

From the above discussion it is clear, insights gained from data is extensively beneficial for business, as they offer new answers for innovation and development. However, achieving data nirvana is no mean feat – the steps highlighted above should be followed, and then only the companies would be able to achieve their desired goal, i.e. a seamless data-driven culture.

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Sources: http://dataconomy.com/2017/05/data-nirvana-develop-data-driven-culture

The role of Big Data Analytics in the World of Media and Entertainment

The role of Big Data Analytics in the World of Media and Entertainment

A reverberating revolution is on the go in the media industry. Reason: thorough digitization and data-driven marketing.

A seamless amalgamation between digital and analytical solutions is transforming versatile media platforms across the globe. Not only does it help in curating more personalized content for its niche audiences, but also bolsters newer capabilities, such as master data management for digital assets and improved customer engagement programs.

Is Big Data Big Enough?

Facebook gathers and processes more than 500 TB of data every day.

Google processes 3.5 billion requests every day.

Amazon records 152 million customer purchase data every day.

With the rise of digitization, media and entertainment companies are leveraging big data technology like no other for better customer engagement.

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Here are a few examples showing how media companies are using the power of big data:

In predicting audience preference

Large chunks of data helps in predicting and understanding the demand of audiences – right from the genre of shows and music they like to content selection for a given age group or for different channels.

Better acquisition and retention

Any day, big data help to fathom the reasons why consumers subscribe or unsubscribe a particular channel. It aids companies in developing robust promotional and product strategies to attract and retain more loyal user base. Social media data also lend a helping hand to enhance consumer interest.

Content revenue generation and new product development

With the power of accurate and productive data, media houses incentivize consumer behavior and while doing so, they understand the true market value of the content generated.

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How Media Uses Data Anaytics?

Netflix

Netflix assimilates large chunks of viewership data, with which it performs an in-depth analysis of viewer’s behavior for millions of viewings of shows. The analysts conduct thorough research on the attributes and qualities of data about consumers to know which show is the most popular. This analysis also helps them know how long viewers are watching a program or season or any individual show. Hence, in this way it outbids its competitors and owns rights to showcase blockbuster hits.

Bollywood

Talking about our very own Bollywood, SRK’s Chennai Express used big data and analytics to boost social media presence and digital marketing endeavors. And, no wonder, it smashed the box office records of 2013. It became such a raging success that the IT services company Persistent Systems released a statement saying, “Chennai Express related tweets generated over 1 billion cumulative impressions and the total number of tweets across all hashtags was over 750 thousand over the 90-day campaign period.”

This is a single instance. Many other bigwig producers have time and again collaborated with cutting edge big data analytics firms to better understand consumer trends and drive customer engagement.

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Conclusion

Big Data is a surefire boon for media and entertainment houses; it helps companies to solve crucial questions about consumers, things they like, content they feed in, and shows they treasure. Moreover, it aids in tracking clicks, shares and views across multiple devices and media platforms.

To lead the change, join DexLab Analytics. Their Data analyst course in Delhi NCR is surely worth taking up to fulfill all your divine career aspirations. Check out business analytics course itinerary now.

 

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How Can You Improve Your Business Figures with Data Lakes

Today, data lakes are springing up here and there. And with that, the composition structure of data lakes is changing. As more and more data are moving towards cloud, data lakes are shifting focus towards cutting edge sources, like NoSQL, while cloud data warehouses are emerging across hybrid deployments.

How Can You Improve Your Business Figures with Data Lakes

A humongous amount of data is being churned out on digital platform each day. IBM says as much as 2.5 quintillion bytes of data is created on a daily basis. Now, this ever-expanding amount of data needs for proper storage system – for that, data lakes have been constructed to hold data in its raw form. In these vast storehouses, data remain mostly in their unstructured state, which is pulled out by data scientists to remodel and transform them into versatile data sets for future use.

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Chief Data Officer Is the Next “Commander” To Join the Digital Kingdom and Here’s Why

Chief Data Officer Is the Next “Commander” To Join the Digital Kingdom and Here’s Why

An over-empowering digital transformation is here and it is wreaking havoc in the C-Suite. CDOs have started taking a front line in managing and pushing new tech like AI and machine learning to alter business landscapes forever.

As a matter of fact, this promising job title has existed for years, even decades – mostly in the financial market. But now when data is being generated at record high speeds, the job role of the CDO is emerging out bigger and better. No more a single person or a general crew is enough to tackle such challenging data issues – to fulfill complicated data management tasks, management is now looking up to specialized data experts.

Gartner predicts that 90% of multinational organizations will appoint a CDO by 2019. Though the first generation CDOs were only concerned about data governance and management, of late, they have been shifting focus on how to best implement data as the best strategic asset in organizations to trigger optimum results.  

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Take a look down to know how CDOs can add value to your organization, while streamlining data and developing strategies:

Be competitive, be ahead of the curve

The best way to ace is by taking over your competitors. In corporate jargon, it means to understand your competitor’s strategies better and arm yourself in the way. Also, it calls up to know your customers better, including the things they like to purchase and know ways you can fulfill their needs. Glean all of these observations with the flattering tool of IoT and machine learning, including social media and supply chain.

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Share information through Data silos

Think how would you feel if you are unable to share information within your department? It can be exasperating. But in reality, it happens. Employees working in the same company, even in the same team forget to share information – data is treated as a commodity that is traded for. That’s why, chief data officers break down data silos in an organization to make sure everyone within the framework get access to data to boost decision-making.

CDOs infuse life into data

All analysts are not good with data. No matter how much they pore themselves over into pie charts and bar diagrams, they just can’t nail it. Machine learning using Python and other related technologies has made things easier – now CDOs can infer trends and draw meaningful insights necessary for a better company future. And mind it these analyses eventually saves hours of production time, millions of losses and much more.

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There’s nothing better than cleaner, fresh data

Unkempt data is no data at all. In fact, data comes handy only when it is clean. Today, with the influx of so many data, organizations falter to keep pace with so much data extravagance data starts becoming dirty or of little use. This results in – every report run is full of flaws, estimates are wrong and lists compiles are inaccurate. As a savior in troubled situations, CDOs help in churning out crystal clear, consistent data by taking care of all the business processes, and making sure that they are properly maintained by the users.

CDOs are the meat and potatoes of C-Suite team

Not only they understand the intricacies of the subject matter, CDOs undoubtedly makes better use of your data, and looks forward to ways to use them in more meaningful manners. They are not here to hoard the data, but to share it extensively among the people working in the organization to produce fascinating results all around.  

Now that you know how important CDOs are, enroll for a reputable business analytics online certification by DexLab Analytics. Business analytics certification is the key to good times, go get one for yourself today!

 

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Where Did I Go Wrong Predicting the Bitcoin Boom?

A few years ago, Silicon Valley in San Francisco came under the influence of a new, mysterious thing known as Bitcoin. It swept away the tech enthusiasts off their feet. There were a wide set of rumors that Bitcoin was virtual money, invented by a pseudonymous math stalwart named Satoshi Nakamoto, who would later stir up the structure of modern finance and render government-powered currency antiquated.

 
Where Did I Go Wrong Predicting the Bitcoin Boom?
 

To understand the phenomenon better, I once bought a single Bitcoin long time back, which then involved a strenuous labor-intensive process, where I had to go to CVS and use MoneyGram to wire dollar value of a Bitcoin to a crypto-currency exchange. After a month or so, I decided to sell it off for a slight loss, thoroughly convinced that this virtual money is nothing but just a passing fad.

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