In the coming years, jobs and businesses are going to be impacted; reason AI. Today’s generation is very much concerned about how the bots will consume everything; from jobs to skills, the smart machines will spare nothing! It is true that machines are going to replace man-powered jobs – by using robots, mundane jobs can be performed in a flick of an eye freeing people working in bigger organisations to innovate and succeed.
Continue reading “When Machines Do Everything – How to Survive?”
Gartner says – By 2020, the global BI and Analytics market is expected to flourish to USD 22.8 billion.
The Global Self-Service Business Intelligence (BI) Market Research Report 2017 provides a comprehensive, detailed analysis of Self-Service BI industry, including the present Self-Service BI market trends and norms. It mainly focuses on the market of big continents, like North America, Europe and Asia, coupled with countries like Germany, US, China and Japan.
Continue reading “Trends to Watch Out – Global Self-service Business Intelligence (BI) Market 2017”
Self Service Analytics is proving useful for business users, who are working on business data without necessarily having a background in technology and statistics. It is essentially bridging the gap between trained data analysts and normal business users.
Self Service Analytics reduces dependency on IT and Data warehousing teams, thereby reducing the turnaround time for a request made by a business user.
It does so by continuously collating and loading real time data into a singular stream without disparity, which is easily accessible through browsers. Thus, it helps business users in taking decisions on Real-Time basis.
This feature benefits organizations because vital decisions made within time can be more profitable as compared to the traditional way of analysing data, which may not be a good idea in respect to the urgency constraint.
Often, the company’s data are fragmented and widespread across various divisions. This increases the headache of channelling the data meaningfully and in a wholesome manner.
Further to this, preparing reports using this data becomes a cumbersome job for the IT department or the department, which is serving such request. Hence, it may lead to increased cost of time or decreased quality of efficiency at which the operations have to run. However, many a times, these reports fail to give an overview of the operations in an organisation.
Self-service BI integrates data from different systems and delivers a “Single Version of Truth”. Accessing this data and running computations on it requires only a browser for access and eliminates the need to install, maintain and administer large-footprint software clients on each user’s workstation.
If Self Service Analytics is hosted on SaaS, it will further reduce the cost of machinery and maintenance associated with it. The provision for usage can be increased or decreased in no time according to the usage pattern. This really means that Self Service Analytics helps you adapt with time and Pay-Per-Use model, which is a leading trend in most of the industries.
Typically, a business user using Excel would have a local copy of data and run computations on it. He can merge and transform it by using various formulas and finally derive a conclusion.
This is dangerous because in live operations, data keeps changing and data integrity is at stake by working on local copies. Thus, accuracy in decision-making becomes a game of luck.
In Self Service BI, the data from the source is extracted, transformed and loaded into a unique data model, which goes with all operations. In this case, data integrity is assured. In addition, all business users have the same source of data, removing the risk that working with different local copies have.
Therefore, from the above stated facts, we can conclude that Self Service Analytics is a need for today’s businesses.
If all the above-mentioned risks are mitigated and proper corporate governance structure is in place, Self Service Analytics can be very beneficial for the success of any organization.
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Appalling forces are re-establishing the relationship between humans and water.
In the past, communities developed slowly, while the weather remained constant. Water sources never depleted at tumultuous rates as it has today. Water is no longer a dependable resource. That’s why many countries and cities are embracing smart technologies to manage water efficiently and preserve it for the coming generations.
As we observe the United Nations World Water Day on Wednesday, 22nd March, it is apt to assess the development being made in conserving this diminishing resource.
Today, the Internet of Things (IoT) – a blooming worldwide network of devices and appliances linked to the internet – has materialized as a propitious solution to save water and protect clean drinking water, especially in cities.
To begin our discussion, Netherlands is on its way to develop a pioneering program to address the relevant problems of increasing sea levels, surging number of droughts and the effect of extreme weather changes on its trains, bus networks and roadways, and the efficiency with which the entire nation tackles situations like this. The ambitious project, Digital Delta draws in local and regional water jurisdictions, top-notch scientists and proliferating businesses to implement Big Data technology for upgrading the systems of its €7 billion water management, while restricting the costs of preserving water by 15%.
Plummeting freshwater resources: a serious challenge faced by the global population is now at its apex. An overwhelming 89 percent of the world population thrives on enhanced water supply systems, which results in a loss of more than 32 billion cubic meters of fresh water, through physical leakage. Thereby, more than 50 percent of world population will be vulnerable in water-stressed regions by 2025. And by 2040, the figures will further push the energy demand by 56%, making US the second highest energy consumer across the globe.
In the meantime, most of the world cities should re-invent and re-structure their assets to pull together advanced functions encompassing different complex systems and to associate with new powerful allies. Urbanization comes with its own costs. Day by day, these networks are growing more complicated and even more expensive. By delving deeper into the interconnections of systems, the societies will be in a better position to grasp how to run them more efficiently.
Water has never grabbed eyeballs, as it has today. Many countries are not at all prepared to manage such burgeoning complexities of water management. Besides, water management authorities are constantly under pressure to harness their power for flood protection and drinking water standards.
New Jersey Institute of Technology (NJIT) revealed that by 2025 smart city technologies would multiply to an industry estimating $27.5 billion. Moreover, nearly 88 smart cities will develop by the end of 2025. Smart cities whirl around the concept of using improved, interconnecting technologies to make environment safe, lives easier and urban living cost-effective and more efficient.
Societies are enduring new weather extremes. It is the high time to use big data and analytical science to cure the growing complexities in managing our water systems. Smart technology is the only viable option that can take future generations towards a sustainable future.
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Do these following questions clog your mind?
I aspire to become a business analytics professional, but I don’t know what skills to possess?
I am sceptical; which training should I opt for in order to establish my career in the sphere of business analytics?
I am looking forward to switch my career into data analytics, but I don’t know which skills to imbibe for better prospects?
Answer: Yes, they do.
Continue reading “Take Small Steps With Big Feet of Business Analytics”
Considering the complex competitive global environment, the world business today is witnessing a paradigm shift from mere data storage to data mining and other subsequent activities.
Thus, from a managerial perspective it is of prime importance to develop a psyche, which can interpret the collection of data. This psyche cannot be theoretically learnt from books, as it requires a knack to make data talk. Data is no more evaluated independently. Today, a cross-domain relationship between data exists, which on analysis depicts patterns, responsible enough to do wonders for the organization.
The question is how can we connect the dots? Following the recent trends, developers are grabbing every opportunity to break a huge chunk of data into meaningful relevant information. From the standpoint of technical professionals, along with an analytical mindset, they need to get hands on experience on the technological perspective to understand the real significance of data evaluation.
Read Also : DexLab Analytics – Training the Future to be Big Data Analytics Fluent
The data not only aligns with the internal activity of the business but also is an integral part for consumer servicing. There is an intense need to study the needs of consumer and every decision he makes, which broadens the outlook of a business on how he/she is using their product. What are the expectations of the customer from an existing product? What more my customer needs? The answers to these questions cannot always be mapped quantitatively but a qualitative approach towards data is one of the key aspects of data analytics.
In this digital era, slightest technological ripples are going to reshuffle the whole industry scenario. And, that is why the omnipresence of data will aid businesses in setting new benchmarks in consumer and market findings. Growing pace of social media would open a Pandora’s Box for companies, who have their right audience in this particular domain.
The emergence of IOT, which primarily thrives on data, will cause disruption in the current business orientation. The data producing sensor architecture directly connected to the company can help the business to be fast and robust, which is the need of an hour. In addition, this analytics might influence mid-size distribution largely.
Simple example of this model: Sensors attached to tyres could sense data, and alert a tyre manufacturer about the usage of a consumer, which will help in servicing their customer at the right moment.
Thus, on an individualistic note there is need to develop a data analytical mindset and include data-ception in perception.
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When you work in the SEO and PPC industry it is a giveaway that you will be handing a large amount of data. While there are several ways you can utilize this data and manage it with Excel functions, and several tutorials are available online to talk about them. But what if you do not have the functions on Excel to do what you have to do with the data. You can use the Visual Basic for Applications (VBA) feature in MS Excel and write your own functions to help Excel carry out the functions that you want it to.
So, here in this advanced Excel training blog post, we will discuss about how to write a simple custom Excel function and will also give you readers some general advice on how to get started with Excel VBA.
First in order to work with the VBA editor in Excel, you must open a new Excel workbook or document and then press the following keys on your keyboard – ALT + F11. This will open a new window on the screen which is the VBE (Visual Basic Editor). This is where you can write your own Excel functions to use with the spreadsheet you have opened in your Excel document. This will be highlighted on the top left corner of the window. The project explorer pane will have the icons for each sheet of the document and another one for the whole of the workbook itself. Then for the next step, right-click on the ‘ThisWorkbook’, and then go to ‘Insert’ and then ‘Module’ options. That will further add a code module along with a container for the code which we will learn to write here.
Now you are ready to write your first Excel function:
Each element of the data gathered through the SEO and PPC will often have keywords and phrases and this can give birth to a large amount of data for people to work with. For a recent piece of analysis, our faculty member was asked to find a method for counting the number of words in a search term. In this way single keywords can be dealt with differently in comparison to phrases. Like for e.g. ‘dresses’ can be treated with a stark difference to the term ‘red party dresses’. But there are often 100s or even 1000s of keywords to work with and it will be too time consuming to manually count the number of words in each phrase. Also there are no in-built functions in MS Excel to do so for us. Hence, we must use VBA to write new functions for us.
This will be the first line of the function you are about to write, start by copying it into the module we just created. Copy it under the words ‘Option Explicit’ which should be anyway entered (if it is not then do not worry, just copy it at the top and we can come to this later). This sentence however, has a lot of important things to tell us about.
Function: this first word itself tells us about which code is going to follow. A function is simply a piece of code that takes one or more values, performs something with them and then returns a different value. For instance, there is a built-in function with Excel called SUM. This function may take some input values and add them together to return a different value which is the sum total of the inputs. Similarly the function we create will take the keywords or phrases as an input and then count the number of words in them, then return a value for that number.
CountWords: we have put this as the name of our function. The moment we wish to use it, we can simply input into the spreadsheet cell the words as ‘countWords’. Just like we would add ‘SUM’ to use the sum function.
Phrases as string: this is the input will be the one to be entered when we will need to search a keyword or phrase.
As integer: this is the type of information which will be returned by the function. We are only interested in the number of the whole words in the phrases and hence are aiming to return an integer value.
The next thing to do is to prepare the function by declaring the variables. Here we will declare the variables in ‘countWords’ as integers because it is built to only take integers. This will allow Excel to warn us if anything unexpected happens. For example, if we want to use a function to count the words in ‘red party dresses’ and it only returns with party. This will mean that something has gone wrong for sure. So, with declaration of the variable we will be able to let Excel know that it is not an integer and hence it will return with an error warning.
The variables we will use in this function are going to be called as ‘I’ and ‘counter’, however, there is no hard and fast rule to name your variables this way, you can name it the way you like. But ‘I’ is usually used as an abbreviation for index and counter will just be used as counter. The next step will be to add this line into your code.
‘Counts number of occurrences of space character in a phraseDim i as integerDim counter as integer: counter = 1
Note that ‘dim’ here is short for dimension. This describes the data type of a variable. We have told Excel through our codes that the variable ‘counter’ will always be an integer. We have also given the initial value as 1. But currently ‘I’ has no value assigned to it. The first line should appear green in the code window, this is mostly because of the apostrophe that precedes it. This line in our code is merely a comment and does not do anything within the code. It only exists as a label to let us know what the use of the code is for. It is a good practice to comment your code as otherwise it often becomes very hard to understand it otherwise. Also feel free to add in your own comments throughout to help understand and all you have to do for it is to add an apostrophe before it.
You must understand that Excel has no preconceived notions about what a word is. So to count them the concept has to be broken down for it to understand in a few short steps. One of the key features of a word is that it has a space either after or before or even at times in between it, and often both.
So we can start by simply telling Excel to count these spaces:
For i = 1 To Len(phrase)
If Mid(phrase, i, 1) = ” ” Thencounter =
counter + 1
End If
Next i
This is one of the key areas of this function, you must paste it or type it out in the code module. You can do so line-by-line as well. But here is an explanation of what is happening with each step:
For i = 1 To Len(phrase)
Here we have given ‘i’ a value, in fact not just one value but a range of values from 1 to Len (phrase). This is a built-in function with Excel that may return the number of characters (letters + spaces) in the phrase we pass it in.
f Mid(phrase, i, 1) = ” ” Then
With this line of the code we are using the ‘Mid’ function in excel. This will ask excel to look into each character in the phrases in turn. This function takes 3 inputs which is – the phrases to be looked at, the character to begin comparison on, and the number of characters to compare with. We aim to compare every letter with one at a time approach. So, we would pass on ‘I’ and 1. And then finally the ‘If’ statement which says that if a character uses spaces, then excel should proceed to the next line of code. Or pass it over to the ‘End If’ statement.
counter = counter + 1
This line is only activated when a space is discovered. So, we increase our counter variables by 1 every time to count the number of spaces in the phrase.
End If
Next i
With the above two lines, we are able to let Excel know where the If statement ends and to go back to the top and the start again for the next value of ‘i’. This is called as a ‘For Loop’ as we letting Excel know that it must repeat this task for a certain number of iterations.
There is also one last piece of code which we will make use of in order to handle a particular situation. When the phrase is passed in is blank. Then copy the following with what you already have:
If phrase = “” Then
countWords = 0
Else
countWords = counter
End If
Here is another statement that we have. If the phrase we input is blank, countWords takes the value 0, or else it will take the value of the ‘counter’ variable. After setting the ‘counter’ to 1 initially, we ensure the code will work for single words. However, it may also return 1 for blank phrases, and this prevents errors from occurring.
End Function
Finally with that we tell excel that we have finished defining our function. Here is the full code as mentioned below, check if yours looks the same or not:
Image Source: us.searchlaboratory.com
After you are done, you can close the VBE by clicking on the ‘X’ in the corner and then going back to the spreadsheet. Once done type in some words in a few cells and then type ‘countWords’ in another cell. And then click one of your cells containing the texts and then close the parenthesis. This cell can now contain the number of words in the cell that we have input. If it doesn’t, then we can set it to ‘automatic’ (Formulas > Calculations Options > Automatic in Excel 2010.
This simple function works best to save time as it can be dragged down over as many cells as you’d like, with hundreds of keywords and phrases. However, you must keep its limitations in mind. We are counting the spaces and not just words.
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While organizations are all words about having data driven decision making to drive their businesses, but maximum of business leaders seem to lack confidence in the information generated from data analytics. But in the rest of the world, demand for analytics training institute is on the rise with every passing day…
Data analysis is increasingly becoming central to decision-making in companies, especially in departments where people work towards increasing customer growth, improving productivity, and risk management. But although companies push to make their decision making process more data dependent, it seems business leaders are still more accustomed to taking serious business based on gut instincts and experiences. They still seem to have trouble trusting the insights shared from meticulous data analysis processes. Continue reading “Data-Analytics Driven Insights Still Distrusted By Executives!”
In the IT world change is always in the air, but especially in the realm of data analytics, profound change is coming up as open source tools are making a huge impact. Well you may already be familiar with most of the stars in the open source space like Hadoop and Spark. But with the growing demand for new analytical tools which will help to round up the data holistically within the analytical ecosystem. A noteworthy point about these tools is the fact that they can be customized to process streaming data.
With the emergence of the IoT (Internet of things) that is giving rise to numerous devices and sensors which will add to this stream of data production, this forms one of the key trends why we need more advanced data analytics tools. The use of streaming data analysis is used for enhanced drug discovery, and institutes like SETI and NASA are also collaborating with each other to analyze terabytes of data, that are highly complex and stream deep in space radio signals.
The Apache Hadoop Spark software has made several headlines in the realm of data analytics that allowed billions of development funds to be showered at it by IBM along with other companies. But along with the big players several small open source projects are also on the rise. Here are the latest few that grabbed our attention:
This open source analytics tool has had quite good impact on the analytics realm, so much so that companies like MapR have even included it into their Hadoop distribution systems. This project is a top-level one at Apache and is being leveraged along with the star Apache Spark in many streaming data analytics scenarios.
Like at the New York Apache Drill meeting in January this year, the engineers at MapR system showed how Apache Spark and Drill could be used in tandem in a use cases that involve packet capture and almost real-time search and query.
But Drill is not ideal for streaming data application because it is a distributed schema free SQL engine. People like IT personnel and developers can use Drill to interactively explore data in Hadoop and NoSQL databases for things such as HBase and MongoDB. There is no need to explicitly describe the schemas or maintain them because the Drill has the ability to automatically leverage the structure which is embedded in the data. It is capable of streaming the data in memory between operators and minimizes the use of disks unless you need to complete a query.
Both big and small organizations are constantly working on new ways to cull actionable insights from their data streaming in constantly. Most of them are working with data that are generated in clusters and are relying on commodity hardware. This puts a premium label on affordable data centric work processes. This will do wonders to enhance the functionality and performance of tools such as MapReduce and even Spark. With the open source project Grappa that helps to scale the data intensive applications on commodity clusters and will provide a new type of abstraction which will trump the existing distributed shared memory (DSM) systems.
Grappa is available for free on the GitHub under a BSD license. And to use Grappa one can refer to its quick start guide that is available readily on the README file to build and execute it on a cluster.
These were the latest open source data analytics tools of 2017. For more such interesting news on Big Data analytics and information about analytics training institute follow our daily uploads from DexLab Analytics.
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