Future-Proof Your Data Game: Top Skills Every Data Scientist Needs in 2023

 

In case you haven't heard, 40% of the workforce is anticipated to acquire new skills during the next three years. It makes sense to do this in order to stay up with the rapid advancement of technology, particularly generative AI. 

However, according to the IBM survey, executives believe that automation and artificial intelligence will require reskilling of 40% of their staff. It also says that in the next three years, a variety of soft skills, business savvy, and analytical abilities will be highly valued. 

I'll go over the most in-demand talents for 2023 in this post, along with how having them can help your career in the long run. 

Now let's get started.Let us begin by discussing the fundamentals for individuals who wish to pursue a profession in data science.

Select a programming language to study and become proficient in. Discover all there is to know about it—its nooks and crannies, its ins and outs. Being an expert in one area rather than a jack of all trades is preferable. 

Many businesses are interested in learning that hiring a person will benefit them in multiple ways. This individual, for instance, is highly skilled at organizing data, but they also excel at producing data visualizations for our board meetings. 

Check out 8 Programming Languages For Data Science to Learn in 2023 if you're not sure which programming language to pick.

Cleaning and organizing data------ 

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Here's how cloud computing will drive future of data analytics

Here's how cloud computing will drive the future of data analytics.

Taking all the cloud capabilities as well as the potential risks that come with  ..

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Revamp of Kochi metro’s data analytics platform on the cards

Accuracy of predictive data on traveling pattern to be improved


Kochi Metro Rail Limited (KMRL) has recommended a few improvements in the data analytics platform that was readied with the help of Rajagiri School of Engineering and Technology (RSET) in order to analyze travelling pattern in the Kochi metro.

The metro agency had inked a memorandum of understanding (MoU) with RSET in 2016 to collate and analyze commuter data based on ticket/travel card-related feeds collected from automatic fare collection (AFC) gates and CCTVs at metro stations. “This considerably helped arrive at commuting patterns in each direction to assess the number of passengers per hour per the direction of traffic [PPHPDT] and the proceeds from ticketing. Face recognition helped estimate how many men, women, and children/students commuted in the metro,” said Father Jaison Paul Mulerikkal, vice principal and professor at RSET.

The emphasis on Artificial Intelligence (AI) helped predict commuting trends in the system of rapid mass transport theoretically by up to 93% accuracy. Efforts are on to further improve the accuracy rate of predictive data. Apart from metro officials, Metroman E. Sreedharan was among those who were keen to know the projections on commuter traffic, he added.

The tie-up between KMRL and RSET got a boost with the Department of Science and Technology approving ₹25 lakh for the initiative. Efforts are under way to take the project ahead by processing commuter data in the respective stations. Efforts will also be made to install AI cameras embedded with chips to aid the entire process. Furthermore, IOT-based sensors could be deployed to assess the structural safety of metro pillars, it is learnt. It will even help forewarn problems like the foundation of a pillar at Pathadipalam sinking, which caused misalignment of the metro track in the area.

Metro sources said a revamp of data collection and analysis process was on, and brainstorming is on about the possibility of extending it to the Water Metro project which will be commissioned later this year.

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Some parts of the world are investing more heavily in data analytics roles than others


Asia-Pacific was the fastest growing region for data analytics hiring among packaging industry companies in the three months ending May.

The number of roles in Asia-Pacific made up 3% of total data analytics jobs – up from 1.5% in the same quarter last year.

That was followed by South & Central America, which saw a 1.4 year-on-year percentage point change in data analytics roles.


The figures are compiled by GlobalData, who track the number of new job postings from key companies in various sectors over time. Using textual analysis, these job advertisements are then classified thematically.


GlobalData's thematic approach to sector activity seeks to group key company information by topic to see which companies are best placed to weather the disruptions coming to their industries.

These key themes, which include data analytics, are chosen to cover "any issue that keeps a CEO awake at night".

By tracking them across job advertisements it allows us to see which companies are leading the way on specific issues and which are dragging their heels - and importantly where the market is expanding and contracting.

Which countries are seeing the most growth for data analytics job ads in the packaging industry?

The fastest growing country was Brazil, which saw 0.2% of all data analytics job adverts in the three months ending May 2021, increasing to 1.6% in the three months ending May this year.

The top country for data analytics roles in the packaging industry is the United States which saw 80.4% of all roles advertised in the three months ending May.
Which cities and locations are the biggest hubs for data analytics workers in the packaging industry?

Some 9.3% of all packaging industry data analytics roles were advertised in Fairborn (United States) in the three months ending May.

That was followed by Westminster (United States) with 8.1%, Broomfield (United States) with 5.4%, and Columbia (United States) with 3.9%.

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FICO Named Best Technology Provider for Data Analytics at 2022 Credit Awards

FICO has developed a unified FICO® Platform for decision management that includes capabilities for data management, analytic development and execution, strategy design and reporting. These capabilities can be shared across different functions, giving users a 360-degree customer management tool. Leading banks across Europe are adopting FICO Platform in order to break through the silos in their organization and propel growth while reducing the costs associated with installing and maintaining different point solutions for each area of the business.

One important capability set that is growing in usage across EMEA is prescriptive analytics, or optimization. This involves the use of advanced, AI-powered analytics to determine customer strategies that meet specified business goals under constraints. Banks across Europe have seen dramatic increases in performance by using FICO optimization to grow the business, manage risk and improve customer satisfaction.

The strength of FICO Platform and its embedded optimization capabilities was acknowledged in late 2020 with The Forrester Wave™: Digital Decisioning Platforms, Q4 2020, an industry analyst report that named FICO as category leader.

“The judges felt FICO was industry-leading in terms of driving change through a single decisioning platform,” said Luke Broadhurst, CEO of Shard Media, which publishes Credit Strategy magazine. “It offered an impressive set of metrics highlighting impact on the customer, with evidence of improved performance and customer outcomes.”

“We are celebrating this achievement, which validates the strength of our vision for a unified decision management platform,” said Matt Cox, vice president and general manager of FICO in EMEA. “From data ingestion to predictive modelling to prescriptive analytics and decision optimization, our platform gives our hundreds of clients across EMEA a real analytic advantage.”

About the Credit Awards

The Credit Awards are known as the leading awards in EMEA for credit professionals, with 30 categories this year. The awards recognise and celebrate innovation, best practice and the hard work of individuals, business divisions and pan-global conglomerates across the entire industry. The 2022 awards were judged by 16 leading figures in the EMEA credit industry.

About FICO

FICO (NYSE: FICO) powers decisions that help people and businesses around the world prosper. Founded in 1956, the company is a pioneer in the use of predictive analytics and data science to improve operational decisions. FICO holds more than 200 US and foreign patents on technologies that increase profitability, customer satisfaction and growth for businesses in financial services, telecommunications, health care, retail and many other industries. Using FICO solutions, businesses in more than 120 countries do everything from protecting 2.6 billion payment cards from fraud, to helping people get credit, to ensuring that millions of airplanes and rental cars are in the right place at the right time.

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WHY IS NETWORK ANALYTICS IMPORTANT IN THE NEW ECONOMY?

As the world becomes more data-dependent, our tolerance for network unavailability or even visible lag is growing. Weak network performance, unlike in previous periods of the digital world, is now a challenge to our productivity, lifestyles, and ultimately even lives. Simultaneously, network infrastructure is growing into a multi-party architecture in which a single data stream interacts with hundreds of distinct providers, any of which could constitute a weak connection between program and user. This is compelling digital enterprises to become more aggressive in their network management and monitoring, fuelling demand for progressively complex and intelligent analytics systems. Here is why Network Analytics is important in the new economy:


Insight into Operations

It’s a basic networking notion that you can’t manage what you can’t see or understand. That’s why many firms are turning to younger generations of AI-powered analytics, which could not only analyze the performance of information faster and more precisely than software systems but can also flexibly shift their focus to spot anomalies and data trends that would otherwise go undetected.

The important part is that current analytics incorporates a wide range of variables to guarantee that networks are not only functioning but also efficient. Furthermore, intelligent analytics, like data patterns, can develop dynamically, which means they can keep up with new deployments and applications without the direct control of developers or network operators.

We may expect the pace of business to pick up in a digital economy, even as profit margins compress and prospects emerge from precisely focused, segmented markets. This means that network resource consumption, load balancing, and a variety of other operations must be moved to near-real-time to make sure that the data and services can be used to their full potential. With 5G networks and the Internet of Things (IoT) linking everything from automobiles to smart sensors, performance degradation would be far more severe than a few seconds of lag while watching the latest viral video.

Equally essential is the opportunity to lower present network administration costs and complexity. However, by installing intelligent agents in network infrastructure, enterprises may rapidly identify the source of any problem, redirect traffic around the impacted systems, and then perform repairs at a far faster rate than in a traditional management system. Even this degree of corrective action will become unusual as the intelligence embedded throughout the system will be able to spot little flaws long before they become huge problems, allowing the remedy to be applied before the client is even aware of the problem.
Honest Networking

On a strictly operational basis, AI does not increase the performance of the network. It can also investigate traffic patterns and other data sets to verify networks are used for their primary purpose and to prevent hacking and data theft.

Organizations can detect patterns disclosing all types of scams using massive data collection and high-speed intelligent analytics, such as fraud rings committing identity theft, falsification, and other offenses, and also attempts to create false identities, take over profiles, and send false information to obtain funds. Furthermore, many of these patterns contain digital traces that allow detectives to track down the culprits.

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Defy Trends Is Bringing Data Analytics To Crypto Investment

The field of crypto investment is fraught with difficulty. There has been an increasing number of crypto scams taking place and most investment is done in the context of media hype and emotional investment.

Even those who keep their funds safe and are immune to hype don’t make the most of what crypto and DeFi have to offer; they are typically not investing based on sound principles or reliable data.

This is where Defy Trends comes in. Recognizing that the market is in need of accurate analytics and a data-based framework for investment, the team behind Defy Trends has created an application that offers a means for responsible and informed decision-making.


Defy Trends Helps To Make Informed Investment Decisions

While fiat trading has a plethora of tools and analytics available to execute trades, this is not the case with cryptocurrencies. Defy Trends fills this void with an application that assigns each coin a score between 0-100. This is not an arbitrary assignment, but a score based on a number of metrics from reliable data sources.

Projects are also individually scored between 0 - 100 on 4 distinct areas: trading score, on-chain score, news score, and social score. So people looking to trade on a certain strategy can place increased emphasis on a given category.

At the very least, this kind of information will help to spot scam coins so users do not waste their funds. Projects without sufficient information are liable to score very low on the Defy Trends index, regardless of what influencers are saying on social media.

“Actionable insights and quality information” is a signature statement from Defy Trends. The information is presented in a user-friendly dashboard so that the investor is not overloaded with data.

Defy Trends is the most advanced set of data analytics on the market that looks at millions of pieces of data from social media, on-chain transactions, community groups, online forums, news, and other sources to produce actionable and digestible indicators.


Crypto Investment: A Maturing Field

Defy Trends does more than offer a tool for informed decision-making. They are building a wider ecosystem that offers rewards for research contributions as well as modules for study. Data analytics are only useful when each analytic is understood in the context of other information.

There is little use in a sea of metrics that the user cannot understand, and this is why it has to be neatly presented with a well-rounded score. Even so, educational content is needed for further clarification.

Defy Trends also provides an Ambassador program. This program empowers women to learn about new technologies and the resulting investment opportunities, so they can achieve their long-term financial goals. It also creates network opportunities so participants can learn more about crypto investment and long-term wealth preservation in a new Web3 era.

The platform further offers solutions for businesses that are looking to get involved in Web3 as well as enterprises that are looking for a set of analytical tools for crypto and digital asset investment opportunities.


Why Data Analytics Are Needed

The days of portfolio managers and legal advisors are, if not numbered, at least going to be completely changed and disrupted. Individuals and businesses alike will need to take more direct control of their short and long-term finances. Crypto investment offers a means to do this, but it’s certainly not automatic; people need to learn how to use the system to preserve wealth.

This requires serious attention to crypto security and continual education, as well as reliable analytics for sustainable investment. This is exactly what Defy Trends provides, with a tool that aims to promote financial freedom regardless of class, ethnicity, background, religion, or gender.

Those who make wealth accidentally never keep it for long. Those who make it systemically and mathematically are practically guaranteed to have more success.

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WHY SYNTHETIC DATA AND DEEPFAKES ARE THE FUTURE OF DATA ANALYTICS?

What is synthetic data?

Synthetic data is data that you can create at any scale, whenever and wherever you need it. Crucially, synthetic data mirrors the balance and composition of real data, making it ideal for fueling machine learning models.

What makes synthetic data special is that data scientists, developers, and engineers are in complete control. There’s no need to put your faith in unreliable, incomplete data, or struggle to find enough data for machine learning at the scale you need. Just create it for yourself.

What is Deepfake?

Deepfake technology is used in synthetic media to create falsified content, replace or synthesizing faces, and speech, and manipulate emotions. It is used to digitally imitate an action by a person that he or she did not commit.

Advantages of deepfakes:

Bringing Back the Loved Ones!

Deepfakes have a lot of potential users in the movie industry. You can bring back a decedent actor or actress. It can be debated from an ethical perspective, but it is possible and super easy if we do not think about ethics! And also, probably way cheaper than other options.


Chance of Getting Education from its Masters

Just imagine a world where you can get physics classes from Albert Einstein anytime, anywhere! Deepfake makes impossible things possible. Learning topics from its masters is a way motivational tool. You can increase the efficiency, but it still has a very long way to go.

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Kerala police to get training in AI, Data Analytics

Synopsis

​​DUK Vice Chancellor Saji Gopinath said this programme marks the next level of e-Governance. 

This is the stage where we start optimizing the processes, 

making the government smart and predictive, or in other words, Intelligent, he said.

HIGHLIGHT : The training programme has 150 hours of classroom sessions that would be handled 

by industry experts and researchers. As many as 15 select officers from the police department 

would undergo the first batch of training, the statement added.

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METAVERSE IN BIG DATA ANALYTICS: WHY CIOS SHOULD BE ON ALERT?

 The Metaverse is reshaping the future of business. Why should CIOs be concerned about the metaverse in big data?

content include :

THE METAVERSE – ENVIRONMENTAL IMPACTS & FUTURE

HOW ARE BUSINESSES USING METAVERSE FOR MARKETING DEVELOPMENT?

HIGH TIME FOR COMPANIES TO HIRE A CHIEF METAVERSE OFFICER?

* The impact of a metaverse in big data analytics

* IT’s the next step in the metaverse

The metaverse is a blend of virtual reality, augmented reality, and mixed reality that will obscure the lines between online and real-life connections. It will end up being where individuals can work, shop, play, and be engaged. A scope of brands from Adidas to Balenciaga have moved into the metaverse, yet past this, there are a few brands that are now exchanging with non-fungible tokens (NFTs) in the virtual world.

In a joint effort with UNXD, an organized commercial center for digital luxury, D&G as of late sent off ‘Collezione Genesi,’ non-fungible tokens assortment that got around US$5.6 million at auction. Hoping to make this non-fungible tokens collection one of many, D&G’s goal is to grant buyers different levels of exclusive brand content and insider access. D&G is leading advancement in its area, perceiving the worth the metaverse can bring to the business, and revealing new information experiences around customer conduct and purchasing behaviors.

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What to expect for data prep and data analytics in 2022

While modern organizations generate astronomical amounts of data every day, many still struggle to make sense of it all. However, that’s gradually starting to change, as more data prep and analytics providers come to the surface to empower nonspecialist users to translate raw data into actionable insights.

In fact, researchers estimate that the Data Preparation Tools Market size will grow at a CAGR of over 20% to reach a total value of $13.15 billion by 2028, with organizations having a range of accessible data analytics providers to choose from, such as Alteryx, IBM Watson Studio, TIMi Suite, and Incorta.


With the data analytics and preparation market in a state of growth, in 2022, more companies those data analytics providers will invest in will develop solutions that give decision makers better transparency over their operational data.
Alteryx acquires data preparation provider Trifacta for $400 million

Data preparation provider Alteryx announced it invested $400 million to acquire visual data engineering cloud platform Trifacta.
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By acquiring Trifacta, Alteryx intends to use its advanced cloud platform to help customers build a more robust data pipeline with greater profiling and preparation capabilities.

It’s worth noting that this acquisition comes after two recent acquisitions, including Hyper Anna, a cloud platform for deriving AI-driven insights, and Lore IO, a data modeling solution.

2021 was a successful year for Trifacta, with the company announcing an annual recurring revenue of $579 million, an increase of 29% from the year before.

A key reason for the organization’s success in the market is its ability to differentiate itself from other specialist solutions by ensuring that non-developers have the option to gain access to meaningful insights.
IBM acquires Envizi, mParticle acquires Indicative

There have also been a number of other notable acquisitions occurring in the data analytics and preparation space. At the start of this year, IBM announced the acquisition of environmental performance management and data analytics provider Envizi for an undisclosed amount.

The acquisition will enable IBM to create more effective supply chain management solutions, while offering greater cover of Environmental, Social, Governmental (ESG) metrics.
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“To drive real progress toward sustainability, companies need the ability to transform data into predictive insights that help them make more intelligent, actionable decisions every day. Envizi’s software provides companies with a single source of truth for analyzing and understanding emissions data across the full landscape of their business operations and dramatically accelerates IBM’s growing arsenal of AI technologies for helping businesses create more sustainable operations and supply chains,” said Kareem Yusuf, general manager of IBM AI Applications in the announcement.

In the future, IBM intends to integrate Envizi with some of its existing solutions including IBM Maximo, IBM sterling, IBM Environmental Intelligence Suite, and IBM Turbonomic.

Similarly, shortly after raising $150 million in Series E funding in November, customer data infrastructure provider mParticle announced it had acquired customer journey analytics platform Indicative.

The company has completed the acquisition in an attempt to help customers gain better visibility over the customer journey, while making it easier to extract data from external data sources like Snowflake.

By augmenting its analytics offering, mParticle will be in a strong position to increase its customer base over the course of the year, which already includes brands like NBC Universal, Spotify, and Airbnb.
Insights are everywhere

Whether an organization wants to monitor ESG goals or the customer journey, there is plenty of data to process, and a growing number of accessible solutions to process it. In 2022, expect to see the number of easy-to-use data preparation tools increase further, as providers aim to break down the barriers to insights.


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Making smarter decisions with data analytics

High-value data and analytics can eliminate the guesswork in healthcare decision-making. Healthcare organizations with strong governance and good data analytics capabilities are better positioned to adapt to value-based care models.

The healthcare industry was starting to recognize the importance of high value data as they moved from fee-for-service reimbursement to value-based care models – but the COVID-19 pandemic made it even more apparent that hospitals need the ability to access and integrate data from multiple sources in order to make meaningful clinical and business decisions. TJ Elbert, Senior Vice President and General Manager of Data at Health Catalyst, said provider organizations, especially, were desperate to access trusted data as they treated patients in a virtual setting.

“There’s a real urgency when you are reliant on monitors and devices to get a full picture of a patient,” he pointed out. “That has increased the need for governance of all that data, from both inside and outside of the hospital, so providers feel like they can trust and then use that data to make decisions that impact care.”

Healthcare organizations with good data analytics capabilities in place, with strong governance, had a much easier time transferring to new models of care as they sought new ways to treat patients outside of the office setting, according to Elbert. In addition, they were also in a better position to make critical business decisions as the pandemic altered what kind of services they were allowed to provide.

“If you are able to use your data, you can better inform virtual care – and pivot to a more digital care model,” he said. “But more than that, you can make smarter decisions across the entire organization. Because when, all of a sudden, elective and outpatient surgeries are gone and you lose that revenue, you need to find a way to come back. Organizations with trusted data could figure out when it was safe to bring those services back, what capacity was needed to be for COVID-19, how to manage patient access to care and how to recover even as things kept changing. Having that information gives you a much fuller picture of what’s happening today – and where you need to be in the future.”

High-value data and analytics, truly, can eliminate the guesswork in healthcare decision-making, said Elbert. Unfortunately, he stated, many organizations still lack the tools to leverage the data they need, whether they are trying to facilitate team-based medicine and care collaboration or understand how to find the money to invest in new surgical technologies that will bolster their bottom line in the future.

“These capabilities can provide you the data to inform you where, when and how to shift – and how to do so in a way that puts your organization where it needs to be from a financial perspective so you are in a position to deliver the care your patients need,” said Elbert. “When you can do this modeling, you can tug on different threads and see what the impact will be, clinically and financially, to solve real problems. Data, really, is the key to allowing organizations to safely move forward with different initiatives – and, in doing so, improve patient outcomes and move the field, as a whole, forward.”

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THE ROLE OF AI, IOT AND DATA ANALYSIS IN CRICKET

 

Data analysis plays a key role in cricket:

We live in a technological age where we are completely surrounded by it. Cricket, as a globally popular sport, could not have been undisturbed by technological advancements for long. The use of technology in cricket has risen steadily throughout time. Third umpires, Hawkeye, and decision review system, as well as power bats and helmet cams, have all been deployed in recent years.

From the comfort of our own homes, we can now watch cricket being played in any region of the world. Our excitement never wanes since technology has made it look so genuine on the screen.

Highlight :Data analysis plays a key role in cricket

Use of AI and IoT in Cricket

SpeculurBatSense

Power Bats

SuperStats

Data Analytics in Cricket

(1. Criclytics,2. CricScience,3. Insights by ESPNcricinfo )

Conclusion : These are just a few examples of how artificial intelligence, internet of things, and big data analytics

are being employed in cricket. In addition to these, Snickometer, Hawk-eye, and Drone Cameras are examples of

modern-day technologies used in cricket.

Technology has revolutionised the entire cricket experience for both spectators and players.

Some regard the increased usage of technology as a threat since it has the potential to undermine

the value of the game. Cricket, on the other hand, is a widely followed sport that cannot be avoided.

Technology and athletics must work together.

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Andhra commercial tax dept to use of data analytics to pick tax evaders

tax evasion | Data analytics | Andhra Pradesh

The Commercial Taxes Department of Andhra Pradesh will use data analytics to pick out tax evaders in the state, a top official said.

The state Directorate of Revenue Intelligence has been tasked with the exercise of carrying out a sector-wise analysis to determine tax collection, plug the gaps and widen the tax base so as to meet the revenue targets.
Special Chief Secretary (Revenue-Commercial Taxes) Rajat Bhargava on Tuesday directed the DRI to work in tandem with the enforcement wing of the CT Department and use data analytics to identify tax evaders.

At a review meeting, the Special CS asked the authorities of the CT Department to strengthen the audit wing to check the compliance levels in the case of large taxpayers.

"We need to ramp up efforts to widen and deepen the state tax base by moving forward in a systematic manner. Focus should be on unearthing large-scale GST frauds," Rajat told the officials.

He also reviewed the state-related issues to be raised at the GST Council meeting, scheduled to be held on September 17 in Lucknow.

The state is yet to get over Rs 2,500 crore as GST compensation this year.

Besides, GST rates on liquor, petrol and diesel, solar power equipment and solar power plants would also be discussed at the Council meeting.

Chief Commissioner of State Tax S Ravi Shankar Narayan, DRI Special Commissioner Ch Rajeswar Reddy and other senior officials attended the review meeting.

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Fascinating Data Analytics Real Life Applications in 2021

To gain such important insight into data as a whole, it is important to analyze data and draw specific information that can be used to improve certain aspects of a market or the business as a whole. There are several applications of data analytics and business are actively using such data analytics applications to keep themselves in the competition. Not only businesses but even civic bodies are using data analysis for several reasons, like monitoring crime.   

Top Data Analytics Applications

1. Security

2. Transportation

3. Risk detection

4. Risk Management

5. Delivery

6. Fast internet allocation

7. Reasonable Expenditure

8. Interaction with customers

9. Planning of cities

10. Healthcare

11. For Travelling

12. Managing Energy

13. Internet searching

14. Digital advertisement

Wrapping Up

It is clear that data analytics applications are taking great strides in almost all avenues across the globe. If we are able to understand data and analyze it, it can help in increasing our overall job efficiency a lot. However, misuse or inefficient use of data can cause several problems and lead to the lowering of overall productivity.

So, it is important that data scientists know how to make use of data efficiently and engage in the right applications of data analytics. If used in the right way, data analytics can bring about a major positive impact on our society and world at large and increase the overall productivity of specific sectors.

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smart-farming-powered-by-analytic

 Fascinating Data Analytics Real Life                     Applications in 2021.

In today’s world, data rules the most modern companies. Numerous packets of data are circulating all around the world due to increasing access to the internet. Businesses are aware that this data translates to information which they can use to improve their customer service, understand trends, or even find market loopholes.

To gain such important insight into data as a whole, it is important to analyze data and draw specific information that can be used to improve certain aspects of a market or the business as a whole. There are several applications of data analytics,

1. smart-farming-powered-by-analytic

Topics covered :

1. Indian Agricultural Sector

1.1 Key problems faced by the Indian Agricultural Sector

2. Smart Farming

2.1. Role of Analytics in Smart Farming

2.2 Use cases of Analytics in Smart Farming

2.3 Analytics in every step of the farming cycle

3. Putting it all together – ‘Smart Farm Operating Model’

4. Global implementations of Smart Farming solutions

5. Key challenges in Smart Farming adoption

6. Addressing key challenges

A key area to be worked upon is the strategy to ensure economic feasibility and ease of adoption. Taking cues from implementations across the world, a prudent approach would be to start small– with pilots in small farming districts. Even though every market is unique, there are learnings from every implementation that can be taken forward. Once, a robust framework is developed, the solution can then be scaled across regions.

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Big Data Security Analytics: A Weapon Against Rising Cyber Security Attacks?

 

1. Security

Data analytics applications or, more specifically, predictive analysis has also helped in dropping crime rates in certain areas. In a few major cities like Los Angeles and Chicago, historical and geographical data has been used to isolate specific areas where crime rates could surge. On that basis, while arrests could not be made on a whim, police patrols could be increased. Thus, using applications of data analytics, crime rates dropped in these areas.

What are the applications of data analytics?

Some of the different data analytics applications that are currently being used in several organizations across the globe are:

1.Security
2.Transportation
3.Risk detection
4.Risk Management
5.Delivery
6.Fast internet allocation
7.Reasonable Expenditure
8.Interaction with customers
Now let's see Cybersecurity in Data analytics

Big Data Security Analytics: A Weapon Against Rising Cyber Security Attacks?
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