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Those of us who don’t deal in analytics on a daily basis don’t really know about the importance of data visualization. Those of us who do, can’t really get enough of it!

We perform analytics to reach actionable insights to fuel our business decisions, making it extremely critical. But how exactly do you get to that insight? With data visualization. Data visualization allows you to present the data and insights generated by the analytics engine in a manner in which it is comprehensible to the end user.

An end user could be anyone. The CEO, operations manager or board of directors. This underlines the importance of data visualization. It is used by almost every decision maker within the organization to arrive at their decisions, through insights.

Data visualization has moved beyond the realm of pie charts and bar graphs. Visualization elements now include sophisticated heat maps and color coded elements. Another important factor is that data visualization makes the data more interactive for the end user, allowing them to delve deep down into the data sets, without losing their way and emerge with actionable information.

Essentially, data visualization helps in bringing out the key points arrived through analytics. It helps present the numbers and figures in a manner in which it makes sense to the end user. Data visualization enables decision makers and analysts to digest massive amounts of data and help spot critical trends and patterns in the business landscape.

Without proper data visualization, it would be next to impossible to derive actionable intelligence from any data. So, here’s why data visualization is considered the backbone of analytics:

  1.  Digest information quickly – Business landscape is continuously evolving, with data playing a key role in that evolution. How fast the information or actionable insights get to the end user depend on data visualization. The ideal data visualization helps illuminate key points in any data sets and fuels decisions.
  2. Zero-in on Patterns and relationships – When presented in the right manner, even huge amounts of data starts making sense, and data visualization plays a key role in that. This allows decision makers to identify relationships and patterns within the business, among competitors and the general business landscape. This helps in market predictions and fuels business critical strategies. This also helps businesses focus on areas that really matter and contribute to the growth of the company.
  3. Know the trends – Data visualization helps present a eagle-eye view of data pertaining to the business and its operating landscape. This helps decision makers pinpoint trends, be it by analysing past data or predicting some future. Data visualization helps in identifying emerging trends, that in turn helps businesses in taking the right decision at the right time to ensure future growth and get a competitive edge over the competition.
  4. Become a storyteller – The best part of data visualization is that it helps analysts tell a story with their data. Once the data points that need to be presented are ready, data visualizations helps analysts communicate the insights using visual storytelling. The end user can interact with the data at a deeper level and comprehend things much more easier than reading through simple strings of data.

Thinklayer offers state-of-the-art data visualization services that complement your existing analytics engines and help fuel business decision with actionable insights. Know more.

The post Data Visualization – The Backbone of Analytics appeared first on Thinklayer.

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Business intelligence and predictive analytics adoption showed a marked increase in 2017, with business intelligence experts and data scientists, working across industry verticals, leading the way.

According to a report released by Dresner Advisory Services, executives and third party consultants are the least likely to rely on business intelligence and predictive analytics.

Enterprises that are dedicated to use business intelligence as a strategic part of their growth strategies are investing the most in analytics reporting, customized dashboards, advanced data visualization modules and end-user “self service”. According to the report, business investment in cognitive business intelligence, text analytics and Internet of Things is still in its emerging stage.

Moreover, enterprises that are turning to custom-made or SaaS business intelligence and predictive analytics tools are preferring certain functionalities related to traditional statistical methods in place – regression models, textbook statistical functions, and hierarchical clustering. Geospatial analytics, which includes use of maps, and recommendation engines also figure high up in their set of requirements.

All in all, when it comes to business intelligence and predictive analytics, enterprises are heavily investing in In-memory analytics, in-database analytics, and In-Hadoop analytics, categorising them critical to their efforts.

Based on this report, it is clear that the industry has started to invest in business intelligence and predictive analytics. However, the rate of investment and adoption is still slow, when compared to other emerging verticals.

Business intelligence and analytics, powered by big data and artificial intelligence, will come to influence boardroom decisions across all industry verticals. Such is the potential of this emerging technology.

Here are some advantages offered by business intelligence:

  1. It is instrumental in removing guesswork from business decisions. Business intelligence helps inform business decisions and helps decision makers chart out a growth strategy for the company. The intelligence provided is churned through tons of business data. It eliminates chance and offers new direction to strategists.
  2. Reports on demand. Decision makers are able to access critical analytics and intelligence in a manner of seconds, from anywhere they are, using any device. Decision makers simply need internet access and a mobile device, like a smartphone, tablet or laptop, to access critical business reports.
  3. Get in the minds of customers. Thanks to big data analytics, the level of insight that businesses now have on their target customers is startling. Business intelligence allows decision makers to analyse tons of customer data and inform their decisions accordingly.
  4. Always on. The scope of business intelligence is such that decision makers can get data-backed, instant answers to their questions. This allows for more informed, and faster decision makers, that are key for any organization’s success.
  5. Understand business better. Business intelligence allows decision makers to get an indepth understanding of their business, by analysing past, present and future data. They also get an insight into the business landscape they are operating in and analyse market competition as well.

Thinklayer offers state-of-the-art business intelligence services, powered by big data and customizable dashboards. Learn more.

The post Companies Must Bet Big on Business Intelligence appeared first on Thinklayer.

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Thinklayer by Natasha Mathur - 1M ago

Big data is powering business decisions across corporate boardrooms throughout the world. Every new product, feature or business these days is built on a foundation of big data-driven actionable insights.

Earlier, the use of Big Data was limited to Fortune 500 giants but now, with the rise of affordable big data analytics tools and the rise of cost-effective data sources, Big Data is accessible to Small and Medium sized Enterprises (SMEs).

But the rate at which SMEs are adopting Big Data is critically low. To survive the competition, to make more informed decisions and to grow, SMEs need to harness the possibilities presented by Big Data.

SMEs can use existing and future Big Data capabilities to zero-in on current trends that are shaping their markets for more informed decisions, analyze their data against their competitor’s to get an edge over the competition and identity future market trends and prepare their strategies accordingly. This and so much more is now possible with Big Data.

Big Data can provide the same opportunities and avenues of growth and expansion to SMEs, like it does to big corporates. In fact, SMEs have an advantage that big corporations don’t have. SME’s operate on the more flexible frame than most of the Fortune 500. This means they are in a better position than big corporates to implement business decisions gained from the actionable insights made available by Big Data.

So let’s go over some of the ways in which SMEs can benefit from Big Data:

1. Know Customers Better – Big Data allows SMEs to know their customers and their audience better. Using Big Data, SMEs can analyze why customers buy, how they buy, when they buy and what do they prefer. But this is not all. SMEs can get in-depth analytics data on their customers’ purchase history and preferences, and plan their product strategies accordingly. Analyzing social media data could also give SMEs insight into how their customers are connected with their brand. The possibilities are endless.

2. Zero-in On Trends – Using Big Data analytics, SMEs can study their own data with the market data and the data on their competition, and identify patterns and trends. This will give them a greater insight into the market landscape and identity and implement future growth strategies.

3. Tweak Operations – Big Data allows SMEs to study their own company in depth, against current and historical performance. This will allow them to zero in on loops and gaps that are having an adverse effect on business growth and tweak their operations accordingly. This will go a long way in improving the operational performance of the company and setting it on the path of growth.

4. Study Competition – Sometimes, the greatest business insights come from studying the competition, to find out what they are doing and how to perfect it for one’s own success. With the easy availability of data, SMEs can study their competition in depth and identify threats or strategies that might give them an over the competition.

Thinklayer offers state-of-the-art Big Data analytics services to Fortune 500s and SMEs, helping them to reach insights that drive business growth. Know more here.

The post Small Business and Big Data appeared first on Thinklayer.

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Thinklayer by Natasha Mathur - 1M ago

Business Intelligence and Data Analytics are mutually interdependent and coexist in the cohesion of each other. For a clear understanding of how to use BI for DA, firstly, we need to understand what BI is, and also what is data analytics and how data analytics is dependent on BI.

Business Intelligence

It is essentially a data-driven decision-making support system. BI is an incorporation of systemic ways and means through which data is collected, collated, analyzed, shared, visualized and reported, all to the aid of better-informed decision-making.

Data Analytics

Data analytics is the supplementing predecessor of BI. Once, we have all relevant data at our disposal and facts presented; this is the time to ask specific questions and glean predictable certainties from it. It is essentially compartmentalizing complex structures into easily agreeable forms for the sake of better understanding of the whole.

How to use BI for Data Analytics

In simpler terms,  in a sequential follow up, organizations ought to do these things necessarily: Once an organization, through Business Intelligence comes to know what is happening to their business, they intuitively explore to know – “Why it is happening?” and furthermore would also like to know “What will likely happen in future?” And here starts the realm of Data Analytics.

While from inception BI stands for – What is happening to your business (for visibility), the preceding questions, i.e., Why it is happening & What will likely occur in future set the stage rolling for the commencement of Business analytics which holistically deals with the investigation, prediction, and prescription. This very process of ‘business analytics’ per se encompasses Data Analytics in its entirety. And the Data Analytics facilitates the process of Business Analytics; this is where the role of Data analytics lies.

Role of Data Analytics in Business Intelligence

Diagnostic Analytics(Why) – In business analytics, to initiate the needful corrective measures, diagnostic analytics comes handy. Through this very process, you differentiate the whole complex structure and come to grasp why a certain thing is happening at a certain place. Now, as you have the requisite information with evidence, you can chart your future course in the best suitable way to avoid failure or enhance performance.

Predictive Analytics (What will) – As from the aforesaid process an organization is well aware of the wherewithal of its products or projects or the organization itself, now, the organization must want to know; by this rate of productivity where we will be heading in the future and if the organization intends to improvise then what would be the required essentials that must be followed or achieved in due course.

Prescriptive Analytics(Next best action) – Now, that the whole state of affairs is known, the intended ‘end views’ are targeted with Prescriptive Analytics. This process of analytics deals with – what is the best suitable set of tactics or strategies that ought to be followed so that in all likelihoods, after a period, we will be in our intended or desired position. Prescriptive analytics is a set of tools through which correctional measures that need to be followed or observed in letter and spirit to define the improvisation that is objectified as goals to be achieved.

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Decisions backed with data are driving businesses forward in this digital age. Good data translates into actionable insights that decision makers use to evaluate and execute strategies. But how to get from A to B?

Data Visualization is the art of representing key data points in simple-to-understand format. Ease of data discovery and insights are key when it comes to visualization. Better the visualization, easier it will be for decision makers and stakeholders to arrive at business-critical insights that can power their strategic decisions.

But the term data visualization is being thrown around so much these days that it has an aura of confusion around it. A visualization can take the form of a bar graph, simple pie chart or a map. But these elements are hopelessly out of date and have limited scope of representing all the key data points due to limits in design.

Data visualization these days is about creating representational elements that allow the viewer to interact with the data, to go deeper into the data without loosing the core objective. Story-based data visualizations unfold in real-time to allow decision makers to get the insight that they need.

Therefore, the importance of data visualization can’t be stressed enough. Be it a small enterprise looking at last quarter’s sales data or a large conglomerate going through multi-geo product launch data, data visualization is relevant for everyone.

Here are some key benefits your business can derive from data visualization:

  1. Bridge the gap between data and insights – Data visualization makes data discovery easier. It effectively bridges the gap between data and the insights you derive from it. The brain comprehends visual representation better than anything else. Data visualizations helps you understand your data better and leads to actionable insights that power strategies.
  2. Discover hidden patterns – The storytelling nature of data visualization helps you zero-in on previously undiscovered operational patterns that could impact business decisions. Data visualization puts key data points into perspective, like comparing historical data with the present. This way, not only new patterns emerge but also important relationships get highlighted.
  3. Get better at trend spotting – Discovering historical, new and emerging trends is one of the key benefits of data visualization. Trends can be unearthed through data visualization depending on the type of visual representation you use. For example, an interactive heat map can allow you to discover opportunities for strategic expansions in other locations.
  4. Talk to the data – The real-time nature of most data visualization tools allows decision makers to interact with the data, allowing them to sift through tonnes of data in mere seconds to arrive at the insight they need. The on-the-go customization functionalities offered by most data dashboards allow flexibility when you interact with the data. Drill down features, which are a core component of a dashboard, allow you get deep inside the data and emerge with actionable insights.
  5. Drive business decisions – Most data analytics tools offer in-built data visualization which is somehow limited in its scope. Custom built data dashboards are more flexible and made for your specific business needs, helping you drive business decisions and growth with the right insights.

Thinklayer offers industry-leading data visualization solutions for clients across the business spectrum. Click here to learn more:

The post How Data Visualization Can Help Your Business appeared first on Thinklayer.

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Thinklayer by Natasha Mathur - 1M ago

How many times have you missed out on key business opportunities due to lack of right data? Or misjudged a particular scenario because a key data point was missed? Data visualization helps stakeholders makes sense of data generated by the analytics engine. Without smart data visualization, business-critical data points would never see the light of day, leaving decision makers scrambling for the right actionable intelligence.

But we don’t need to tell you all this. What you really want to know is how to make the most of data visualization tools at your disposal. So here’s a list of top 10 data visualization tips that will make data discovery easy, fast and efficient.

  1. Simplicity is Key: Before you take the dive, decide which data points are relevant and which ones you can do without. The visualization of the output will be clutter-free and easy to interpret if you discard unrelated data points, making it easier for you to understand your data.
  2. Don’t try to make your data “pretty”: When data visualizing, focus on elements that will allow easy data discovery and interpretation, rather than the ones that will make the presentation look “pretty”. You might prefer an element that is aesthetically pleasing but doesn’t showcase the critical insights and key figures.
  3. Go for layers: Using layers to represent different data points will allow you not only to make the data more story-based and communicative, but will also prevent the end-user from becoming overwhelmed. For layering, rely on drill downs, links and shortcuts for easy data discovery and navigation.
  4. Talk to stakeholders: Who is the end-user? The stakeholder(s), who are supposed to interpret the data and make business decisions. Sit down with them and learn what they want out of the final report. This will allow for goal-based data visualization, and you will end up giving the stakeholders what they want and improve the business decision making process.
  5. What is the viewing device?: When designing data visualization elements, know on which device the stakeholder will be viewing the data. Is it a mobile, a tablet or a laptop? A data visualization designed for a laptop might now come out right on a mobile or a tablet for that matter and vice versa. The design should work equally well across all device platforms.
  6. Select the right chart:  All data visualization charts are not the same. Choose the chart most capable of presenting the kind of data you have. Selecting the wrong data chart will make the information less impactful and might hide key data points the stakeholder is looking for.
  7. Don’t go crazy with the colors: Colors are an effective way to highlight the difference between data points and aid in faster data discovery. However, when used with abandon, they can have the opposite effect. For example, it is ok to use bright colors to highlight the most important aspects of a report, but using bright colors all over can make the stakeholder lose focus and miss out on a key insight.

Thinklayer offers tailor-made visualization services for organizations of all shapes and sizes. Learn more here:

The post Top 7 Tips for Data Visualization appeared first on Thinklayer.

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Data analytics continues to evolve at a staggering rate, what with the arrival of Artificial Intelligence and Machine Learning in the picture. As the data analytics market evolves, visualization of data has become key.

Taking into perspective the amount of data generated and analyzed, it is imperative that the data be visualized in a manner in which data discovery becomes simple and decision makers are able to make sense out of it. This is where data visualization tools come in.

Data visualization tools take the raw data generated by big data and analytics data engines and present it in a numerical and graphical format, housed in dedicated, custom-made dashboards. Each dashboard can be fine-tuned on the basis of data and intelligence needs and industry-defined or role-specific KPIs.

Interactive data visualization tools are big on ease-of-use, offering intuitive navigation, drag-and-drop options and simple data structuring options. The ideal visualization tools is also big on connectivity, being connected to all the relevant data sources so that the user doesn’t run dry in the middle of analysis. Last but not the least, a data visualization tool should be flexible enough to adjust to your business domain. Essentially, it should have the capability to create custom dashboard based on industry-specific KPIs.

Here is a list of top 5 tools that fit all the above criterias and are winning at big data and analytics data visualization.

  1. QlikView: QlikView is a guided analytics and dashboarding solution that has been steadily revolutionizing the data discovery and visualization landscape since its launch. QlikView is an insight-driven tool that allows you to create flexible guided analytics applications. When it comes to usability, QlikView scores big, allowing you to create custom application using its own script. Data is beautifully represented and it is easy to integrate QlikView with existing business applications using dedicated APIs. QlikView gives you complete control of your data, allowing top-down control access, data privacy & security and data management.
  1. Tableau: Tableau is a world leader in data visualization. The best part about Tableau is that you don’t need any coding experience to find your way around the software. Tableau is available in desktop, mobile and cloud versions, with the basic version being freely available at most academic institutions. Simple, interactive dashboard allow you to zero-in on actionable insights. Data connectivity is aplenty as Tableau offers support for everything from big data platforms and SQL database to cloud-based apps like Google Analytics and Salesforce. Its exceptional drag and drop features enable deep data analysis and visualization, leading to actionable insights on-the-go. As far as visual representation goes, Tableau covers all the bases. One feature that stands out is its mapping tool, which allows you to represent your data on maps of more than 50 countries on the basis of postal codes.
  1. Microsoft Power BI: Power BI is Microsoft’s answer to data visualization tools that have flooded the market. Microsoft Power BI bills itself as a business analytics tool designed to deliver insights to your organization. But it is so much more than that. Biggest advantage you would have with Microsoft Power BI tool is that its data connectivity options. On this tool, you can source data from a multitude of sources including all of Microsoft’s enterprise offerings, Oracle, Salesforce, Google Analytics, MySQL, Adobe Analytics, GitHub, MailChimp, the list is endless! It is not too far behind when it comes to data visualizations. You can create custom dashboards with a single click and convert raw data into actionable reports that can be shared across the organization. Data management, privacy and data security features can in-built Microsoft Power BI and it scores high on compliance.
  1. ClearStory: ClearStory offers no nonsense data visualization solutions. The tool offers none of the gimmicky features but all the analytical and visualization capabilities you can get. ClearStory’s solution is highly scalable and flexible, offering targeted data visualizations that offer quick actionable insights. The visualizations offered by ClearStory’s platform takes into account the data’s size, source, shape and semantics. Every feature is tied to the central aim of aiding in data discovery, exploration and interpretation.
  1. Dundas BI: Dundas BI by Dundas Data Visualization is a browser-based business data analytics and visualization tool that is taking the market by storm. The tool allows you to create integrated dashboards, perform complex data analytics and also offers best-in-class reporting tools. Offering cutting-edge data visualization tools, Dundas BI allows you to create interactive dashboards using industry-specific KPIs. Users have often cited the tool’s ability to drill-down to the required data and generate insight-oriented visualization.

Thinklayer offers data visualization solutions designed to help you track key metrics and KPI’s and obtain actionable insights through custom dashboards. Learn more about our visualization services here. Thinklayer Visualization Services

The post Top 5 Tools That Are Winning At Data Visualisation appeared first on Thinklayer.

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The data churned by the analytics engines gets presented for the end-user or stakeholder on the dashboard. Therefore, the critical nature of the dashboard can’t be stressed enough. An effective business dashboard allows easy data discovery and lets stakeholders zero-in on actionable insights in a matter of seconds.

There are many ways in which you can create an effective dashboard. For example, judicious use of colors, shape elements, charts can be used to make a dashboard highly interactive and communicative. The foundation of every great dashboard is built from answers to three key questions: Who is the dashboard for, how will the dashboard add value, and what type of dashboard are you creating.

If you have not considered these 3 key questions then it is time you did. Business dashboards are there to get the pulse of the business, define future strategies and foresee market trends. Here’s how to develop a result-oriented visualization dashboard using these 3 key questions.

Who is the dashboard for?

This is the first thing every dashboard designer considers before creating a dashboard. Knowing your audience or the stakeholders involved will give a direction for dashboard design and will reveal newer ways of presenting the data.

Learn who the end user is and what information he/she is looking for. A field sales operations managers would be interested in viewing the team’s sales figures and time spent on ground by each member rather than viewing how the company’s stock is performing. Similarly, if your end user is the CEO, he/she will be looking for a bird’s eye view of the organization’s performance rather than getting into the day-to-day operational data.

However, you won’t always create the dashboard for a single audience. You might end up making a common dashboard for the entire organization. As every stakeholder’s information need will be different, you might face difficulty in visualizing the data. The best way to tackle this is to prioritize the stakeholders and design your dashboard around that.

How will the dashboard add value?

Before designing a dashboard, learn first what kind of information you will be presenting and the type of business process the information is related to. Analyse the information and business process in-depth to know what type of data is important and which is not. For example, for a dashboard related to in-store sales, you would want to present the sales figures based on individual locations and a grand sales figure, alongside sales targets and quarter projections. If you end up showcasing sales staff attrition figures on a sale dashboard then it won’t make any sense.

What type of dashboard you are creating?

The design of your dashboard will depend on the type of dashboard you are creating. Although there are multiple type of dashboards when it comes to design, there are three basic types you will encounter: Operational Dashboards, Executive Dashboards & Analytics Dashboard. An operational dashboard covers the operations side of the business, from data on website performance to inside sales figures. An executive dashboard contains information for the decision makers. Lastly, an analytics dashboard contains vital information for strategy building like an executive dashboard but also features drill down elements to allow stakeholders to get in-depth information about the business.

The key to unlock data is through visualizations like reports, metrics, KPI’s and dashboards. Thinklayer offers state-of-the-art visualization services to organizations across the spectrum. Learn more here: Thinklayer visualization services

The post How to Develop Visualization Dashboard For Best Results appeared first on Thinklayer.

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Data is the new oil. This is the new jagron that companies are following. Back in 2015, the amount of data generated was pegged at 5.6 Zettabyte. Let that sink in. Now imagine the deluge of data that will be generated in 2017. For decision makers, this poses a statistical nightmare as they need to interpret data in real-time to gain and implement actionable insights.

This is where data visualization comes in. Data visualization tools make data discovery easier, making sure that business-critical information doesn’t slip through the cracks. Based on custom or industry-defined KPIs, managers can develop custom dashboards that interpret and present data relevant to business, in real-time.

The importance of data visualization can’t be stressed enough. So here are 5 reasons why you should invest in data visualizations right now, if you are not doing it already.

  1. Key Business Trends can impact product or service pipeline
    Data visualization brings out hidden facets in your data sets to reveal relevant past or future business trends that are critical to your decision making process. Relevant insights into customer behaviour or market landscape can allow you to tweak your service or product pipeline to generate a measurable impact. Not only this, data visualization could open up new business or product avenues by bringing out the relevant information that might have escaped you in the past.
  2. New ways to discover data
    Data visualization tools offer you new formats or techniques with which you can visualize and discover the information you need. Data visualization in the form of heat maps, fever charts or other forms of graphical visualization can bring out hidden data points that might have been absent in previous representations, giving instant actionable information to decision makers. Data discovery is key when it comes to analytics and data visualizations facilitates that better than simple reports.
  3. Identiy business patterns
    Spotting critical business patterns or relationships is key when it comes to decision making. Data visualization enables you to have a 360 view of business and operational data to help you spot patterns or relationships that are affecting your business processes. For example, dipping customer satisfaction could be tied to rising exit rate of customer care executives. By viewing this data, a decision maker could implement strategies to stem the exit rate and hire more executives to service customers.
  4. Direct Interaction
    With data visualization, your data doesn’t hide behind 1D charts and reports, but is out there on the dashboard for you to discover, digest and gain actionable insights that can be pivotal in decision making. Data visualization allows a direct, one-on-one interaction with the data, tapping in multiple resources and working around set parameters to represent data in the most easy-to-understand manner.
  5. Make decisions faster
    The real-time nature of data visualization allows you to discover valuable insights almost instantly, making decision making a much faster process. Key business opportunities are lost if the right information is not available in the right time and data visualization plays a major role in this. Data points like customer sentiment, sales volume of a particular product, performance of competitor’s products can be viewed instantly and acted upon swiftly.
  6. Run What-If Analysis
    The key essence of data visualization is that it gives you future prespective. You can run various What-If analysis on dashboards and based on current data you can see the various cases that can be possible.

Thinklayer offers tailor made visualization services based on your organization sector which decides the key KPI’s essential for your organization. Learn more about our visualization services here.

The post 5 Reasons Why You Should Invest in Data Visualisation appeared first on Thinklayer.

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Data analytics continues to evolve at a staggering rate, what with the arrival of Artificial Intelligence and Machine Learning in the picture. As the data analytics market evolves, visualization of data has become key.

Taking into perspective the amount of data generated and analyzed, it is imperative that the data be visualized in a manner in which data discovery becomes simple and decision makers are able to make sense out of it. This is where data visualization tools come in.

Data visualization tools take the raw data generated by big data and analytics data engines and present it in a numerical and graphical format, housed in dedicated, custom-made dashboards. Each dashboard can be fine-tuned on the basis of data and intelligence needs and industry-defined or role-specific KPIs.

Interactive data visualization tools are big on ease-of-use, offering intuitive navigation, drag-and-drop options and simple data structuring options. The ideal visualization tools is also big on connectivity, being connected to all the relevant data sources so that the user doesn’t run dry in the middle of analysis. Last but not the least, a data visualization tool should be flexible enough to adjust to your business domain. Essentially, it should have the capability to create custom dashboard based on industry-specific KPIs.

Here is a list of top 5 tools that fit all the above criterias and are winning at big data and analytics data visualization.

  1. QuilkView: QuilkView is a guided analytics and dashboarding solution that has been steadily revolutionizing the data discovery and visualization landscape since its launch. QuilkView is an insight-driven tool that allows you to create flexible guided analytics applications. When it comes to usability, QuilkView scores big, allowing you to create custom application using its own script. Data is beautifully represented and it is easy to integrate QuilkView with existing business applications using dedicated APIs. QuilkView gives you complete control of your data, allowing top-down control access, data privacy & security and data management.
  2. Tableau: Tableau is a world leader in data visualization. The best part about Tableau is that you don’t need any coding experience to find your way around the software. Tableau is available in desktop, mobile and cloud versions, with the basic version being freely available at most academic institutions. Simple, interactive dashboard allow you to zero-in on actionable insights. Data connectivity is aplenty as Tableau offers support for everything from big data platforms and SQL database to cloud-based apps like Google Analytics and Salesforce. Its exceptional drag and drop features enable deep data analysis and visualization, leading to actionable insights on-the-go. As far as visual representation goes, Tableau covers all the bases. One feature that stands out is its mapping tool, which allows you to represent your data on maps of more than 50 countries on the basis of postal codes.
  3. Microsoft Power BI: Power BI is Microsoft’s answer to data visualization tools that have flooded the market. Microsoft Power BI bills itself as a business analytics tool designed to deliver insights to your organization. But it is so much more than that. Biggest advantage you would have with Microsoft Power BI tool is that its data connectivity options. On this tool, you can source data from a multitude of sources including all of Microsoft’s enterprise offerings, Oracle, Salesforce, Google Analytics, MySQL, Adobe Analytics, GitHub, MailChimp, the list is endless! It is not too far behind when it comes to data visualizations. You can create custom dashboards with a single click and convert raw data into actionable reports that can be shared across the organization. Data management, privacy and data security features can in-built Microsoft Power BI and it scores high on compliance.
  4. ClearStory: ClearStory offers no nonsense data visualization solutions. The tool offers none of the gimmicky features but all the analytical and visualization capabilities you can get. ClearStory’s solution is highly scalable and flexible, offering targeted data visualizations that offer quick actionable insights. The visualizations offered by ClearStory’s platform takes into account the data’s size, source, shape and semantics. Every feature is tied to the central aim of aiding in data discovery, exploration and interpretation.
  5. Dundas BI: Dundas BI by Dundas Data Visualization is a browser-based business data analytics and visualization tool that is taking the market by storm. The tool allows you to create integrated dashboards, perform complex data analytics and also offers best-in-class reporting tools. Offering cutting-edge data visualization tools, Dundas BI allows you to create interactive dashboards using industry-specific KPIs. Users have often cited the tool’s ability to drill-down to the required data and generate insight-oriented visualization.

Thinklayer offers data visualization solutions designed to help you track key metrics and KPI’s and obtain actionable insights through custom dashboards. Learn more about our visualization services here.

The post Top 5 Tools That Are Winning At Data Visualization appeared first on Thinklayer.

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