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A Guide To Different Types Of Business Analytics

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A Guide To Different Types Of Business Analytics

Businesses today can no longer afford to run based on assumptions, they need actionable intel which can help them formulate sharper business strategies. Big data holds the key to all the information they need and the application of business analytics strategies can help businesses realize their goals. Business analytics is about collecting data and processing it to glean valuable business information. Business analytics puts statistical models to use to access business insight. It is a crucial branch of business intelligence that applies cutting edge tools to dissect available data and detect the patterns to predict market trends and doing business analysis training in delhi can help a professional in this field in a big way.

Different types of business analytics:

Business analytics could be broken down into four different segments all of which perform different tasks yet all of these are interrelated. The types are namely Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. The role of each is to offer a thorough understanding of the data to predict future solutions. Find out how these different types of analytics work.

Descriptive Analytics: Descriptive analytics is the simplest form of analytics and the term itself is self-explanatory enough. Descriptive analytics is all about presenting a summary of the data a particular business organization has to create a clear picture of the past trends and also capturing the present situation. It helps an organization to understand what are the areas that need attention and what are their strengths. Analyzing historical data the existence of certain trends could be identified and most importantly could also offer some valuable insight towards developing some plan. Usually, the size of the data both structured and unstructured are beyond our comprehension unless it is presented in some coherent format, something that could be easily ingested. Descriptive analytics performs that function with the help of data aggregation and data mining techniques. For improving communication descriptive analytics helps in summarizing data that needs to be accessible to employees as well as to investors.

Diagnostic Analytics: Diagnostic analytics plays the role of detecting issues a company might be facing. When the entire data set is presented comprehensively, it is time for diagnosis of the patterns detected and detecting issues that might be causing harm. Now, this business analytics dives down deeper into the problem and offers an in-depth analysis to bring out the root cause of the problem. The diagnostic analytics concerns itself with the problem finding aspect by reading data and extracting information to find out why something is not working or, working in a way that is giving considerable trouble. Usually, principle components analysis, conjoint analysis, drill-down, are some of the techniques employed in this specific branch of analytics. Diagnostic analytics takes a critical look at issues and allows the management to identify the reasons so that they can work on that.

Predictive Analytics:  Predictive analytics is sophisticated analytics that is concerned about taking the results of descriptive analytics and working on that to forecast probabilities. It does not predict an outcome but, it suggests probabilities by combining statistics and machine learning. It takes a look at the past data mainly the history of the organization, past performances, and also takes into account the current state and on the basis of that analysis it suggests future trends. However, predictive analytics does not work like magic, it does its job based on the data provided and so, data quality matters here. High quality, complete data ensures accurate prediction, because the data is analyzed to find patterns and further prediction takes off from there. This type of analytics plays a key role in strategizing, based on the forecasts the company can change the sales and marketing strategy and set a new goal.

Prescriptive Analytics: With prescriptive analytics, an organization can find a direction as it is about suggesting solutions for the future. So, it suggests the possible trends or, outcomes, and based on that this analytics can also suggest actions that could be taken to achieve desired results. It employs simulation and optimization modeling to predict which should be the ideal course of action to reach a certain goal. This form of analytics offers recommendations in real-time, it could be thought of as the next step of predictive analytics. Here not just the data previously stored is put to use, but, real-time data is also utilized, in fact, this type of analytics also takes into account data coming from external sources to offer better results.

Data Science Machine Learning Certification

Those were the four types of business analytics that are employed by data analysts to offer sharp business insight to an organization. However, there needs to be skilled people who have done Business analyst training courses in Gurgaon to be able to carry out business analytics procedure to drive organizations towards a brighter future.


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Summer Internship/Training 101

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Summer Internship/Training 101

Hard Fact: Nowadays, all major organizations seek candidates who are technically sound, knowledgeable and creative. They don’t prefer spending time and money on employee training.  Thus, fresh college graduates face a tricky situation.

Summer internship is a quick solution for them. Besides guaranteeing a valuable experience to the fresh graduates, internship helps them secure a quick job. However, the question is what exactly is a summer internship program and how does it help bag the best job in town?

What Is a Summer Internship?

Summer internships are mostly industrial-level training programs for students who are interested in core technical industry domain. Such internships offer students hands-on learning experience while letting them gain glimpses of the real world – following a practical approach. Put simply, summer trainings enhance skills, sharpen theoretical knowledge and are a great way to pursue a flourishing career. In most cases, the candidates are hired by the companies in which they are interning.

The duration of such internships is mostly between eight to twelve weeks following the college semesters. Mostly, they start from May or June and proceeds through August. So, technically, this is the time for summer internships and at DexLab Analytics, we offer industry-relevant certification courses that break open a gamut of job opportunities. Also, such accredited certifications add value to your CV. They help build powerful CVs.

If you are a college student and from Delhi, NCR, drop by DexLab Analytics! Browse through our business analytics, risk analytics, machine learning and data science course sections. Summer internships are your key to success. Hurry now!

Deep Learning and AI using Python

Why Is It Important?

Summers are crucial. If you are college-goer, you will understand that summertime is the most opportune time to explore diverse career interests without being bogged down by homework or classroom assignments.

Day by day, summer internships are becoming popular. Not only do they expose aspiring candidates to the nuances of the big bad world but also hone their communication skills, create great resumes and make them super confident. Building confidence is extremely important. If you want to survive in this competitive industry, you have to present a confident version of you. Summer training programs are great in this respect. Plus, they add value to your resume. A good internship will help you get noticed by the prospective employers. Always, try to add references; however, ask permission from your supervisors before including their names as references in your resume.

Moreover, summer training gives you the scope to experiment and explore options. Suppose, you are pursuing Marketing Major and bagged an internship in the same, but you are not happy with it. Maybe, marketing is not your thing. No worries! Complete your internship and move on.  

On the other hand, let’s say you are very happy with your selected internship and want to do something in the respective field! Finish the internship, wait for some time and then try for recruitment in the same company where you interned or explore possibilities in the same domain.

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It’s no wonder that summer internships open a roadway of opportunities. The technical aptitude and in-demand skills learned during the training help you accomplish your desired goal in life.

For more advice or expert guide, follow DexLab Analytics.

 

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What Does a Business Analyst Do: Job Responsibilities and More!

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What Does a Business Analyst Do: Job Responsibilities and More!

A flamboyant, sophisticated technology lashed with a heavy stroke of sci-fi, AI and machine learning – is today’s data science. To manage, control and understand such an elusive concept, we need highly skilled data specialists – they must have mastered thoroughly the art and science of machine learning, analytics and statistics.

As the world is becoming more dynamic, the roles of data analysts and professionals are found to be increasingly inclined towards precision, versatility and eccentricity. More and more, they are expected to do things differently, posing as catalysts for change. They play an incredible role in inspiring others and bringing accuracy and accountability within an organization.

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Data Analysts Facilitate Solutions for Stakeholders

“Business analysis involves understanding how organizations function to accomplish their purposes and defining the capabilities an organization requires to provide products and services to external stakeholders,” shares International Institute of Business Analysis in its BABOK Guide.

The main job of a business analyst is to understand the current situation of a company and facilitate a respective solution to the problem. Mostly, a team of analysts work with the stakeholders to define their business goals and extract what they expect to be delivered. They gather a long range of business-fulfilled conditions and capabilities, document them in a collection and then eventually frame and strategize a plausible solution.

Analysts Have a Multifaceted Job Role

Mostly, they wear many hats as the tasks of analysts are widely versatile and always changing. Below, we have mentioned a few most common job responsibilities they have to perform every day:

  • Understand and analyze business needs
  • Address a business problem
  • Construe information from stakeholders
  • Fulfill model requirements
  • Facilitate solutions
  • Project management
  • Project development
  • Ensure quality testing

Enjoy a smooth learning experience from a reputed analytics training institute in Delhi – DexLab Analytics!

The Title ‘Business Analyst’ Hardly Matters

As a matter of fact, the title ‘business analyst’ doesn’t matter much. To fulfill the role of a ‘business analyst’, you don’t have to an analyst at the first place. Many execute the tasks as part of their existing role – data analysts, user experience specialists, change managers and process analysts – each one of them can feature business analyst behaviour.

Put simply, you don’t have to be a business analyst to do the job of a business analyst.

Business Analysts Act As Interpreters

As always, different stakeholders have different goals, needs and knowledge regarding their businesses. Stakeholders can be anyone – managers to end users, vendors to customers, developers to testers, subject matter experts, architects and more. So, it depends on the analysts to bring together all this knowledge and analyze the information gathered. This, in turn, offers a clear understanding of company goals and vision. It bridges the gap between the business and IT.

For this and more, business analysts are often compared with interpreters. Just the way the latter translates French into English – analysts too translate their stakeholders’ query and needs into a language that IT professionals can easily grasp.

Hope this comprehensive list of thoughts has helped you understand what analysts do in general!

If you want to become a data analyst or interested in the study of analytics, drop by DexLab Analytics. They are a one-stop-destination to grab data analyst certification. For more, reach us at dexlabanalytics.com

 

 The blog has been sourced from ― elabor8.com.au/what-does-a-business-analyst-actually-do

 

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How Students Select a Good Data Science Course?

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How Students Select a Good Data Science Course

Data science and analytics are in hype. This time, we decided to know what students look for while arming themselves in this new age field of study. For that, we bring you Analytics India Magazine’s recent survey.

We are on an interesting endeavor to tap into the key areas that IT professionals and aspiring candidates look up to for lessening the learning gap. Ready to join us?

Disclaimer – the below opinions are from budding data scientists – from young IT employees to fresh graduates; we have compiled them and presented in a concise way. All thanks to AIM.

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What key element to consider in a data science or analytics course?

For students, there are many preconceived notions about a course’s curriculum, faculty, brand name and even fellow batch mates. No wonder, it’s always tricky to focus only on a single key element.

Nevertheless, going by the survey, the respondents voted the most for course content, only to be seconded by hands-on experience. Yes, course content is the life and soul of data science and analytics training program. But, it’s not enough, it has to be supplemented by good hands-on experience and placement opportunities.

For more,

What should be the duration of the data science or analytics course?

Short-term or long-term? This is a very common question plaguing the minds of interested candidates –in the recent survey, more than 66% of respondents said they would choose short-term programme over long-term, and almost 55% said that they would prefer part-time skill-training programme than full-time.

What format would you chose for data science training courses?

Always, course curriculum should be in an easy to learn format. When the expert guys at AIM asked the respondents what kind of format do they prefer for their educational course, this is what they revealed:

  • 47% or more voted for a hybrid format of education
  • 28% said they prefer online learning method
  • Less than 25% of the candidates said they would like to stick to the old-school classroom method of teaching

What about Capstone Projects and Placements?

Capstone Projects are important. 92% of respondents vouched for that.

Another 57% said that placements are crucial too if you are thinking of making a mark in the competitive tech industry. Up-skilling is the key in today’s world.

When is the best time to opt for a data science course?

There’s nothing like the best time to enroll in a data science and analytics course. Anytime, you can start learning. However, the 43% of respondents believe that it’s better to take up business analyst training course right after graduation or post graduation.

On the other hand, 33% think that gaining some work experience prior to start training would be helpful.

For more such updates, watch this space.

If you are looking for a decent data analyst training institute in Gurgaon, DexLab Analytics fits the bill right. Drop by their site and gather information.

 

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

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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.

Looking for a good analytics training institute in Delhi? Visit DexLab Analytics.

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 from — datanami.com/2018/08/13/empowering-citizen-data-science

 

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

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#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?

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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

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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?

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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.

Accelerate your career with business analyst training Delhi NCR. DexLab Analytics offers 360-degree Data Science Online training in Delhi – interested candidates please visit the website.

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

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