Data science news

Maximising the value of big data analytics

BIG data technology has impacted our lives in multiple ways in recent years. By analysing large amount of data, scientists, governments and businesses have been able to make important discoveries that have improved our standards of living and changed the way we live and work. Companies today use big data analytics as a way to discover trends to improve the way they conduct business and bring value to stakeholders. Big data sets can go up to several terabytes in size. It can be challenging to analyse massive amounts of data, especially when organisations are under pressure to deliver.

The need for insights is often time-sensitive too, which means that data needs to be interpreted quickly and accurately to enable better decision-making. Without the appropriate tools, managing and analysing big data becomes a frustrating and time- consuming process. Here are a few ways how organisations can maximise the value of their big data analytics.
1) Blend data
2) Help leaders help themselves
3) Visualisation is key
4) Plan for the future

Using Analytics to Discover the Business in Your Data 

Every year, the amount of data being created continues to grow at a tremendous pace. According to IDC, by the end 2015, the global annual rate of data production is expected to reach a staggering 5.6 zettabytes. Businesses can either use this ocean of information to grow faster or miss the opportunity.

Businesses looking to put their data to use, need to bring together their Big Data and Enterprise Data Streams so that all the data can be seamlessly accessed and analyzed.

It’s also prudent to adopt a 2-way approach to gain most from your data – use data to seek operational insights that will help you achieve business goals, and explore your data to uncover hidden trends and patterns.

To maximize the impact of your data analytics efforts, it’s essential to put a strong foundation in place. It involves 3 steps:

Align functional areas around business goals
Create a data supply chain
Use a data discovery platform

Why Data Visualization Is Becoming An Important Legal Trend

The amount of data that we create, store, and distribute is growing at a crazy rate. Anyone who has done document review for more than an hour knows the effect this has on litigation – the contract drafts, the calendar requests, the group e-mails, the reply alls to the group e-mails, the interoffice memos, etc. Every time someone hits Reply All to a large group e-mail to say “Thanks!” or “Ok! Got it!”, some doc reviewer gets 15 more minutes of billable time. It all adds up and creates a bunch of data that needs to be reviewed.

For most people on the doc review team, the focus is just sorting and organizing – putting everything into little piles until the case settles or the next project comes along or the documents run out. But for the people who actually need to use the data, sometimes having 50,000 documents tagged “knowledge of danger” is of little use because it still leaves you with a big pile to sort through. So, as more data gets accumulated, the legal community needs to look at more creative ways to sort and organize it so that it can actually be used.
That’s where data visualization comes in. Data visualization is kind of a nerdy term for the awesome concept of adding art, creativity, and math together to visually digest huge chunks of data.

5 Tips for Using Data Analytics to Grow Your Small Business

1) Goals: This is a necessary first step that provides you the ability to track and maximize your progress and success. Ensure everyone is pursuing the same goal and clearly communicate next steps and deliverables to the team.
2) KPIs: Key Performance Indicators are a group of important metrics that you’ll be monitoring the closest. Choose to evaluate metrics that contribute to company change and growth.
3) Start small: Begin to monitor your KPIs and measure that progress over time. There is no need to introduce all of the data at once which can be cumbersome and overwhelming.
4) Tools: With endless third-party analytical tools available on the marketplace, make sure you find the one that works best for your organization. Your decision will ultimately depend on the goals and KPIs that you’ve established earlier in the process.
5) Manage change: Based on what the data shows, some changes may be needed in order to continue to grow your small business. This may require you to streamline current processes, create new systems and communicate this change with the team – all of which requires you to manage.

Data science news

Drowning In Big Data – Finding Insight In A Digital Sea Of Information 

In today’s digital world, big data finds relevance across industry, government, science, public health and academia, however gaining insight from all this information has been challenging for most, until recently. According to an article published in 2014 by Harvard Magazine, entitled ‘Why “Big Data” is a Big Deal’, improved statistical and computational methods that involve linking datasets, visualizing data, and creating “big algorithms”, are the key innovations that will enable us to wrestle all this data to the ground. Taking cues from physicists and astronomers, who have long since worked with huge datasets, data scientists and social scientists are combining the quantitative with the qualitative to gain insight from big data. Big data analysis is actually creating a new field, with Harvard’s School of Engineering and Applied Sciences working toward offering a master’s in Data Science.

4 Ways Interactive Data Visualization Enhances Digital Marketing 

Marketing techniques are often loud, annoying, and in your face. It’s gotten to the point where most consumers simply ignore these techniques, forcing marketers to come up with new ploys to entice customers. A new and exciting trend in digital marketing that consumers love is interactive data visualizations.

Here are a few of the most prominent ways interactive infographics are enhancing online marketing strategies across the board:
A Break from Data Dump
Data Becomes Engaging
More Shareable Content
Increases Visiting Time on Site

3 Ways Data Viz Fuels Better Customer Service 

The mobile device has transformed itself from serving rudimentary roles like SMS, alarm clock to complicated services like mbanking, mhealth, meducation etc. that it performs today. In light of this change, mobile has become a cornerstone of the global economy leading to new dimensions for business.

Thriving customer service drives business success. Happy and engaged customers save you money in the long run. In fact, it’s ten times more expensive to gain a new customer than retain the customers your business already has.
But, it’s harder than ever to keep customers loyal, as competitors are just a click away. Businesses need to pay attention to the customer service side of the business in real time—and data visualization enables that competitive advantage.

Keep customers around longer, and increase overall customer service, engagement and loyalty. Here are three ways data visualization can improve critical customer service and engagement KPIs.

1. Track and Improve Net Promoter Score
2. Visualize Brand Attribute Surveys
3. Maximize Customer Engagements

What Can Big Data Ever Tell Us About Human Behavior?

We are now solidly in the era of big data, where computers are capturing and processing the details of everything we do with all our interconnected devices in real time. Businesses see this as the Holy Grail for finally being able to predict who, where, and when customers will buy their existing solutions, and what their future solutions must look like to be attractive.

For me, the first step in understanding the potential is to better understand what human data really looks like as it comes in from all these sources. I found some help in this regard from a new book, “Humanizing Big Data,” by leading consumer researcher Colin Strong. I will paraphrase here the keys ways he outlines that our lives are becoming increasingly datafied:
Datafication of emotions and sentiment
Datafication of relationships and interactions
Datafication of speech Datafication of offline and back-office activities Datafication of culture